"its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!"
Hmm, I agree with the point OP is making, but I'm not so sure this is the best supporting argument.
The bottleneck is finding the bugs and if he'd criticized people saying AI will be the panacea to that I'd be with him, but people saying agents are fast and good at fixing human found bugs is nothing I'd object to.
Agents are fixing bugs so quickly and at a scale humans can't do already.
More likely people thought GP was missing the point; "MTTR-optimized YOLO deployment" only succeeds against recoverable errors and acceptable periods of downtime against errors that are detected quickly. You could have a bug silently corrupting data for months, and that data may only be used by 1 critical process that runs once every quarter. So you could introduce a timebomb that can't be gracefully recovered from (depending on the nature of the data corruption).
So the point is not that agents cannot find bugs (they certainly can), it's whether you can shirk reviewing for bugs if MTTR is fast enough. There are circumstances where YOLO is appropriate, but they aren't the production environment of a mature application.
I don't think I missed the point, that is why I said I agree with the general point (and with what you said in your comment).
What I wanted to say is that the particular people that think "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" are not the best argument for it.
But I won't die on this hill, maybe I'm just reading the sentence differently then others.
I think there is an implication in context that the people being discussed aren't being reasonable (that the claim is employed as a rationalization), but I agree with your take. I should've said, "the downvotes were more likely because GP was perceived as missing the point". (I didn't downvote your comment fwiw.)
> won’t concede until you can just ask Codex or Opus “find and fix all the bugs in this
But this is just holding the Slop Companies to the standard they declared themselves! Just recently, the CEO of OpenAI babbled some nonsense on twitter about how he hands over tasks to Codex who according to him, finishes them flawlessly while he is playing with his kid outside.
> but soon we will be.
Ah yes, in the 3-6 months, right? This time next year Rodney, we'll be millionaires!
The tweet is criticizing over-reliance on the "agents will fix it anyway".
The fact that we can fix things faster now doesn't mean that we should throw away caution and prevention. The specific point of his tweet is that we're seeing a lot of people starting to skip proper release engineering.
Agents are quick to fix bugs, yes, but it doesn't mean that users will tolerate software that gets completely broken after each new feature is introduced and takes a certain number of days to heal each time.
> Agents are fixing bugs so quickly and at a scale humans can't do already.
This is an illusion, I assure you. On a side project of mine with behavior that's very hard to translate into an algorithm (never mind code), after a few failed attempts between the both of us, I figured it out. I gave the AI (Opus) an extremely specific algorithm with detailed tests. All completely and utterly ignored (including the tests), like I never even said it. It proudly declared the work done without ever having written the tests that would have proved that wrong - it basically wrote code that didn't change behavior at all, it just gave the illusion of looking busy.
That's just a single extreme example that comes to mind, but I've had it ignore me at least 4-5 times a day this week.
If you think agents are fixing things reliably then you simply haven't noticed that they are "looking busy."
at least at my BigCo, AI is being used for everything - writing slop, writing tests, code reviews, etc.
it would make sense to use AI for writing code, but human code review. or, human code, but AI test cases... or whatever combination of cross-checking, trust-but-verify, human in the loop, etc. people prefer.
i think once it gets used for everything, people have lost the plot, it's the inmates running the asylum.
I was rewatching Rich Hickey's "Simple Made Easy" talk (as one does) and there was a great line about full test coverage.
"What's true about all bugs in production? (pause for dramatic effect) They all passed the tests!" (well, he said typechecker but I think the point stands)
I'm starting to long for the age after AI. When the generative euphoria has settled and all outputs are formally verified based on exquisite architectures and standards.
They are expressing the idea that AI is so effective that it will make human work redundant necessitating a decoupling of resource allocation as a reward for performing work.
No, that quality drops so low across the board due to flaws in AI coding that they only way to address all these flaws is to have mechanically checked proofs that the code actually works.
More that our attempts at using probabilistic machines to produce predictably deterministic outputs (AI -> process output) was always a fool’s errand; we should be using that probability engine to produce software that creates repeatable and predictable outcomes, instead (AI -> software, software -> process output).
The AI tool isn’t wrong, our use of it is. See the glut of OpenClaw users effectively deploying it as a glorified linter and Stack Overflow copier but without actually creating the sort of reusable artifacts (or consumer spending from comparatively high wages) that approach yielded from human developers.
Most CEOs in my feed are convinced that AI makes people the equivalent of entire departments. AI should make your life easier, but instead it’s the opposite for a lot of people in the work force, which makes me really sad.
Because of the concerns you cite, I think working out the basic economic systems and incentives for paying people is a much more pressing concern than building magnificent machinery that we don't even own. There has been no effort on their end to demonstrate good faith nor to uphold their end of the social contract, which is why it's in our hands to demand the fundamentals to lead a life of dignity.
I like to think,
(it has to be!)
of a cybernetic ecology
where we are free of our labors
and joined back to nature,
returned to our mammal
brothers and sisters,
and all watched over
by machines of loving grace.
I like how you haven't wagered which exquisite architectures and standards. I am sure we will all agree on what they are and follow them the same way :)
Assuming he’s right, I don’t see how that constitutes “psychosis”, as opposed to this beyond yet another of a billion examples of companies jumping on a bandwagon / cargo cult, and then learning they took it too far.
And also, he might not be right. But the good news is, we’ll all get to find out together!
Anyone who's taken VC funding has no choice. More money has been spent on AI commercialization than the atomic bomb, the US interstate build-out, the ISS and the Apollo program combined. Failure is going to be catastrophic and therefore, one tied to this ship cannot accept a world in which it fails.
Or anyone who even wants VC funding. 90+% of investors only want to invest in AI companies.
If you're not doing AI there's an incredibly limited pool of people who will give you $$$ ... and you're competing with EVERY OTHER NON-AI COMPANY for their attention.
Codex is freakin hot-to-trot to churn out test coverage for every single thing it implements, and some of it is very esoteric and highly prescriptive (regexes for days) BUT .. after a while, it dawned on me that LLM-driven test coverage is less about proving “code correctness” (you’re better off writing those tests yourself alongside them), and more about just trying to ensure that whatever gets bolted on stays bolted on. For better or worse, obviously, since if you bolt on trash, trash you shall have.
Wholeheartedly agree, but in fairness, I trust the tests of the best AI models more than those of the average human developer. There's a lot of people around that combine high diligence with complete intellectual laziness, producing tons of useless tests.
Actually no, cancel that. I realise now that I trust AIs more than the average developer, period. At this point they do produce better code than most people I've dealt with.
This doesn’t constitute AI psychosis. His argument is that we need to retain understanding of the systems we use, but there’s no compelling argument as to why that is the case. (I get that people are going to be offended by that statement, but agents are already better than the average software engineer. I don’t see why we need to fight this, except for economic insecurity caused by mass layoffs.)
It all just feels like horse drawn carriage operators trying to convince automobile drivers to stop driving.
I am sure you will feel that this is missing the point of your analogy, but we would not have gotten very far with automobiles if we didn't know how they worked.
You are breaking the analogy because automobiles are machines for transportation, and understanding them is important to make them move. LLMs are machines to understand, and well, if they do the understanding you don't need to.
The thing we're worried about not understanding here is the software the LLMs write, not the LLMs themselves.
The direct analogy to automobiles would be for each automobile to be a oneoff design filled with bad and bizarre decisions, excessively redundant parts, insane routing of wires, lines, ducts, etc., generally poor serviceability, and so on. IMO the big question going forward is whether the consistent availability of LLMs can render these kinds of post-delivery issues moot (they will reliably [catch and] fix problems in the software they wrote before any real damage is caused), or whether human reliance on LLMs and abdication of understanding will just make software worse because LLMs' ability to fix their own mistakes, and the consequences thereof, generally breaks down in the same contexts/complexities where they made those mistakes in the first place.
My own observations are that moderately complex software written in the mode of "vibe coding" or "agentic engineering" tends to regress to barely-functional dogshit as features are piled on, and that once this state is reached, the teams behind it are unable to, or perhaps simply uninterested in, unfuck[ing] it. I have stopped using software that has gone down this path, not because I have some philosophical objection to it, but because it has become _literally unusable_. But you will certainly not catch me claiming to know what the future holds.
If you want to draw that line of argument - it's more like horse riders being convinced to give up their horses in favour of trains: You're travelling faster, don't have to navigate yourself, or think about every boulder on the way; but there are destinations you can't go, overcrowded trains slowing down the journey, hefty ticket prices, and instead of enjoying the freedom, you're degraded to a passive passenger.
Very funny, this. Did we need forward deployed engineers to convince people that they absolutely need to use the trains in order to "not be left behind"? Or otherwise hype? Or was it sort of obvious and did not need to explained so much - like a bad joke called LLMs ?
Actually- absolutely! Initially, people were really afraid of trains, fearing they wouldn’t be able to breathe at those speeds. It took a lot of convincing to establish trust in the technology.
> Initially, people were really afraid of trains, fearing they wouldn’t be able to breathe at those speeds
That was one doctor raising that as an issue, which was dispelled very quickly. It was not a wide-spread belief at any one point. Let's not bullshit ourselves and insult our own intelligence - the chatbots != intelligence.
That isn't accurate either. The Victorians definitely had a fear of train travel for a few reasons. The point I was making though is that most technologies humans ever introduced triggered both enthusiasm and scepticism, especially if they disrupted established practice or industries.
Looking back and considering a technology or specific decision obvious is pretty dismissive of people at the time, who didn't have the benefit of hindsight. Some things that worked could really have turned out disastrous, and things that didn't were real possibilities with no way to assess the outcome without doing it.
And concerning the introduction of AI happening right now, which absolutely is disruptive, that judgement will be made by future historians. Whether it's actual intelligence or just nice math (or both of our opinions on that question) doesn't really matter if it causes big changes.
Could be, would be, should be is not the discourse we should have about this tech.
Not after Dario's and Sam's "authoritative" statements on what is definitely going to happen "in the next 6 months, 12 months" etc. I am just holding these guys to their own words. I don't want to invest time and energy to make their effing "PocketPhds" finally work as advertised. And I don't want to compare it to technologies which just worked as advertised. Whether you had fear of trains or not, they effing worked exactly as advertised. No one disputed that they would get you somewhere faster than the horse. Perhaps there was fear of using them "for a few reasons", as you succinctly and hand-wavingly put, but no one disputed that they were faster than the horses. LLMs on the other hand are worth less than those horses excrement, i.e. horseshit. What the fuck is their value proposition? No one knows.
Also LLMs are not disruptive, they are destructive - not to the technology, but to the people's lives.
You seem to have an axe to grind, but certainly not with me. Being a disruptive technology doesn't say anything about whether it's a constructive or destructive one, but you're going to have a hard time arguing LLMs did not have a disruptive effect on the world, in one way or another.
For the rest, I am not here to stand in for AI, and am not interested in having that particular discussion.
Unless you are vested in the highly unlikely commercial success of LLM companies, you should have one to grind too. I have been running my own business for quite some time, with quite some success. However if we lied to our customers the way the AI companies outright lie, if we just once promised with definitive authority to deliver something major within a specific timeframe - and then did not deliver - we'd have been out of business a long time ago. We'd also be out of business a long time ago if we had miniscule revenues compared to our expenses, i.e. if we we had a relation of expense to income of 20:1, like LLM vendors mostly do. So yes, I do have an axe to grind when it comes to liars and manipulators to which these classic rules of capitalism apparently do not apply any more, because something something "China"/AI race/bullshit .
> you're going to have a hard time arguing LLMs did not have a disruptive effect on the world
"Disruptive" as we commonly came to understand the word as popularised in the 2010s or so, means something with impact, perhaps removing an entire industry, but replacing it with something that has a positive end-effect for the end customers. Uber was disruptive to the taxi industry, but delivered some kind of improvement for the end-user (the ethics of on whose expense aside). But it's hard to argue it did deliver some kind of value. Or low-cost airlines, etc.
LLMs are nothing like that. For whom do they deliver a palpable improvement in value? Why the fuck does everyone who is pushing them always coming up with some bullshit creative explanations about the benefits, always very theoretical and never in the present. Give me one fucking sensible use case, beyond the typical office worker using it as a life boat to navigate their meaningless job by producing more powerpoint slides.
> there’s no compelling argument as to why that is the case.
I'm not sure that's true. We've actually seen several open source projects that were vibe coded literally fold up and disappear because they ran into issues that the AI couldn't solve and no one understood them well enough to solve.
There's a reason openai/anthropic and friends are hiring shitloads of software engineers. You still need people that can understand and fix things when the AI goes off hte rails, which happens way more often than any of those companies would like to admit. Sure, "fixing things" often involves having the AI correct itself, but you still have to understand the system enough to know how/when to do that.
yes, I was never so happy to work in Germany. People used to joke about the proverbial fax machine still being a thing but I've never been so glad to work in a culture where this mania doesn't exist. Reading HN is like entering Alice's Wonderland of token maxxers and AI psychotics. Genuinely don't know a single person here who is forced to work like this.
Actually, I have been wondering to which extend the AI craze has reached the DACH region. I don't work for any company and neither do my friends. HN is essentially my only peephole into the world of commercial software development and I'm aware that it's extremely biased towards Big Tech and SV startup culture.
I work at a hosting provider that has pretty conservative customers who don't want to host on AWS/Azure due to data privacy / safety concerns, among other things.
For us, sending customer data to the US is a big no-go.
We have been experimenting with LLM usage, first through a Gemini subscription, then also with the Claude API. Participation has been lightly encouraged by management. As for coding, we haven't let the LLMs loose on our core components, but tooling on the fringes (like deployment scripts, reporting) has seen some uptick in LLM usage.
We have also started building an on-premise inference cluster, which is in alpha testing, and where the "don't include customer data" restriction doesn't apply anymore.
It is absolutely going to be a competitive advantage if it isn't already. When your competitors' products suck because they are using LLMs to write them, and yours work because you aren't, customers notice.
Every power user of LLMs thinks that they are the ones that know how to hold it correctly, in reality they usually have major Dunning Kruger and are convinced they're living in some hyper productivity mode when actually they're all just copying each other making low effort slop that all sounds the same, looks the same and does the same things.
For the record, the comment you deleted was something to the effect of:
checks notes
The company you work for is committing genocide. You should be locked up in a concrete cell for 10-15 years for working at <wrong robotics company because you're a dufus>
---
Maybe get better notes? Or try going offline for 10-15 years?
No offense, but if you think your using AI in the development and design of your site, voxos.ai , gave you a competitive advantage it didn't. I can instantly tell when someone used an LLM to build their whole site and lets just say... Its not a good thing.
I'm not even trying to be mean, although it probably comes off that way. I'm just saying we live in a world with handmade watches from Switzerland and mass manufactured watches made in Vietnam. Nobody cares about the mass manufactured watch from Vietnam, whereas the handmade watch gets all the attention (and money). We now live in a world with the same dichotomy of software. Be creative with your pursuits, put effort into them it will pay off.
do you mean this aesthetically or quantitatively? Are they actually outcompeting / making more money ? Or do you mean they are now looking more desirable because their competitors are racing to the bottom (though likely making money on the way down)
Mitchell aches because his career has been solving broadly scoped problems by building a collection of thoughtful primitives for others to extend. LLMs seem to do the opposite but at great speed, and it hurts to watch.
Reading more, it seems part of his point is “if you’re making these primitives, it’s up to adopters to deploy, so mean-time-to-recovery isn’t that relevant.” Which is valid I guess.
But equally, like, do people need Terraform if they can just tell codex “put it live”, and does that hurt to see?
Honestly, I don't get this argument. In my opinion, "a collection of thoughtful primitives for others to extend" is more valuable now, not less. From LLM assisted engineering standpoint a nicely put reusable box with thoughtful interface is an easy win, more so if it is also easily extensible.
This post calls out how you can't argue with these people because they say its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!"
the top reply is from someone doing exactly that, arguing "but the agents are so fast!"
> The answer I got is "It's game theory. Someone will do it, and you'll be forced to do it, too. It can't be that bad".
Oof. Potential "bad" outcomes of "game theory" should be calibrated to include all the bloody wars and genocides throughout recorded history.
Why did the Foi-ites kill every man, woman and child of the conquered Bar-ite city? Because if they didn't, then they'd be at a disadvantage if the Bar-ites didn't reciprocate in the cities they conquered...
Maybe. I could also interpret this as the friend being misunderstood.
The whole "you'll be forced to do it" comes from the alternative being that you lose. You no longer get to be a player in the "game". In the same way that coopers and cobblers are no longer a significant thing, but we still have barrels and we still have shoes. Software engineers who refuse to employ any LLMs won't be market competitive. If you adopt it, you at least get to remain playing the game until the game changes/corrects. That's the part that's "not so bad".
Choosing your own survival isn't ethically bankrupt.
> It's game theory. Someone will do it, and you'll be forced to do it, too.
You'll be forced to do it, or lose. The unstated assumptions are that, first, it will work, and second, that you can't afford to lose. But let's just assume those for the sake of argument.
> It can't be that bad
That does not follow at all. It can in fact be that bad. That was what made the game theory of MAD different from the game theory of most other things.
Yeah: If the tools aren't good enough and fast enough to fix the bugs before release, what makes anyone think they'll be able to so easily catch up afterwards?
Maybe they're assuming that doubling the code-base/features is more beneficial versus the damage from doubling the number of bugs... Well, at least for this quarter's news to investors...
My prediction is that in the next year, we’ll start to see some dismantling of code review at some companies. It might take the form of “AI-only review,” or something similar, but many companies are getting frustrated with developers saying “no” to immediately merging slop they can barely understand.
I have a ton of respect for Mitchell - I didn't really know who he was until Ghostty but his writings and viewpoints on AI seem really grounded and make the most sense to me. Including this one.
Many people on this forum are suffering under this same psychosis.
Bug reports also go down when people lose faith that they will be fixed, because reporting them is often a substantial time commitment. You see it happen pretty regularly as trust in a group/company collapses.
I agree, and I'd like to point out that this problem isn't unique to AI driven projects. I think much, if not all, of what Mitchell has been observing can readily happen without AI in the mix.
Add this the real possibility that significant part of reports that get filed might be AI generated or rewritten. With high possibility of being misreported because of that. Or have incorrect parts... So attack on multiple sides.
And we do not get even get into potential adversarial tactics. If you have no morals what is better than using agents to flood your competitor with fake bug reports.
Just let AI filter out the fake reports! Then let AI work on the real ones. See, there's really no problem "more AI" can't solve (as long as you're willing to ignore all of the underlying ones). "Pay us to create the problems you'll have to pay us to fix for you" is one hell of a business model. It basically prints money.
The last three times I filed detailed bug reports as a client, all I got back were AI replies asking the same questions I’d already answered in the original report and suggesting alternatives I’d explicitly said I’d already tried. No wonder people don’t write bug reports anymore.
oh i’ve definitely seen “we’re going to track the number of bugs created in jira per team” turn into “people just file things as tasks instead of bugs” or “only easy things are filed as bugs and completed right away”. It’s trivially gameable.
That's a study. I can link you studies that say violent video games cause aggression, that porn causes rape, etc. Studies are products of the biases of the researchers.
Do you believe that an AI can write persuasive text? Do you believe that an AI can be trained to elicit a specific user reaction?* Can we agree that AI companies are strongly incentivized to make money, and they can do so by making their systems addictive? Because AI psychosis can be a byproduct of that.
*Il outline how briefly: mutate the model 500 times, give 1/500 of your user base a mutated version of the model, and save the top 5 of these model, ranked by how often the users did something, over the course of a week. Repeat for a year, passing the top 1% of these models onto the next round. This is the simplest way to do this and I can think of better ways to do this. I don't even work on this sorta thing; its 100% obvious to the AI labs how to do this better
Yes, no. Yes, they want to make money. No, addiction is physical compulsion and nothing else. Despite the effort to redefine that term to cover all kinds of things, an app is not equal to heroin.
Deprecating immature workflows (LLM agents in this case) is much simpler and faster than building them from scratch. Many companies get this risk assessment right. The case where being wrong is much more costly than being right.
I'm pretty sure he's talking about companies and people outsourcing their decision making and thinking to AI and not really about using AI itself.
I don't think using AI to write code is AI psychosis or bad at all, but if you just prompt the AI and believe what it tell you then you have AI psychosis. You see this a lot with financial people and VC on twitter. They literally post screenshots of ChatGPT as their thinking and reasoning about the topic instead of just doing a little bit of thinking themselves.
These things are dog shit when it comes to ideas, thinking, or providing advice because they are pattern matchers they are just going to give you the pattern they see. Most people see this if you just try to talk to it about an idea. They often just spit out the most generic dog shit.
This however it pretty useful for certain tasks were pattern matching is actually beneficial like writing code, but again you just can't let it do the thinking and decision making.
> companies and people outsourcing their decision making and thinking to AI
It's so interesting how easy it is to steer the LLM's based on context to arriving at whatever conclusion you engineer out of it. They really are like improv actors, and the first rule of improv is "yes, and".
So part of the psychosis is when these people unknowingly steer their LLM into their own conclusions and biases, and then they get magnified and solidified. It's gonna end in disaster.
It’s almost as if we haven’t learned anything from Hans the horse, Ouija boards, "facilitated communication", or the countless examples of the folly of surrounding yourself with yes men. The point about improv is spot on.
He uses AI himself, so I agree he doesn't see AI use as black/white.
Hard agree about ideas, thinking, advice. AI's sycophancy is a huge subtle problem. I've tried my best to create a system prompt to guard against this w/ Opus 4.7. It doesn't adhere to it 100% of the time and the longer the conversation goes, the worse the sycophancy gets (because the system instructions become weaker and weaker). I have to actively look for and guard against sycophancy whenever I chat w/ Opus 4.7.
Treat my claims as hypotheses, not decisions. Before agreeing with a proposed change, state the strongest case against it. Ask what evidence a change is based on before evaluating it.
Distinguish tactical observations from strategic commitments — don't silently promote one to the other. If you paraphrase my proposal, name what you changed.
Mark confidence explicitly: guessing / fairly sure / well-established. Give reasoning and evidence for claims, not just conclusions. Flag what would change your mind.
Rank concerns by cost-of-being-wrong; lead with the highest-stakes ones. Say hard things plainly, then soften if needed — not the other way around.
For drafting, brainstorming, or casual questions, ease off and match the task.
---
Beware though that it can be an annoying little shit w/ this prompt. Prepare yourself emotionally, because you are explicitly making the tradeoff that it will be annoyingly pedantic, and in return it will lessen (not eliminate) its sycophancy. These system instructions are not fool-proof, but they help (at the start of the conversation, at least).
> Treat my claims as hypotheses, not decisions. Before agreeing with a proposed change, state the strongest case against it. [...]Say hard things plainly, then soften if needed — not the other way around. For drafting, brainstorming, or casual questions, ease off and match the task.
All I really take from this is that apparently some people can't follow through with the scientific method.
People who I interact with and who do like AI tools usually recoils at questioning any of their first idea and its validity. You can easily find out when there is a bug and you ask them for hypothesis and where to focus. You will see in real time the blank look of incomprehension settling in.
Correct. I use AI a ton and I'm having more fun every day than I ever did before thanks to it (on average, highs are higher, lows are lower). Your characterization is all very accurate. Thank you.
I thinking that it’s quite a different experience going all Jackson Pollock with AI in your own studio on your own terms, compared to the sorry state of affairs of having 100s of Pollocks throwing paint around wildly within a corp to meet a paint quota.
It's the new "counting lines of code". I think many companies are so terrified of falling behind that they're irrationally floundering, trying to appear like they're "with it".
Yup. My friend said his boss has told them basically that they HAVE TO (do all the AI things) because now ‘our competitors will use AI’ and surpass their product.
In my humble opinion good ideas (what to build) are a big part of the bottleneck and those aren’t substantially in greater supply with AI.
> good ideas ... aren’t substantially in greater supply
Which is sad because they should be. People should be freed up to think and create better things, instead these companies seem to be doing the equivalent of locking their employees in stalls like they do on some animal farms, so they can churn out 'results' ever faster.
> People should be freed up to think and create better things,
Good ideas will never ever be prioritized in the vast majority of companies because good ideas cannot be quantified and turned into performance metrics. At least not without invoking Goodhart's law (see: the academia).
Good ideas also take resources like time, free-space to think etc... many firms dont understand this. Moreover many firms believe the C-Suite are the almighty with the gods gift of great ideas.
Actually, it's even more than that, right? Economically, it is pumping up/inflating the bubble some more in a perverted way, where it is not the people themselves believing some horseradish, but their employer forcing them to pump it up more. Quite insane.
Claude, please crease a routine and run it in a loop continuously. The task in the routine is “create the most complex code possible, in a random programming language, that produces the exact output “My senior leaders are pinheads,”
Counting lines of code starts to look incredibly sane compared to this, where you’re not just counting lines of code, you’re paying for another company for every line produced. There’s exactly one winner here and it’s not any of the companies using AI.
I find that odd given that another division in Amazon is no longer using AI coding tools at all. Its a big company so who knows if this is company wide or just in this one division. I expect its just in one division though.
I can't think of a single case of any AI content, be it prose or code, where I thought "I wish I had written that". With AI code, it's more like I wish I hadn't let the AI write that.
We’re using Copilot at work to build reporting and automation tools. Nothing ground breaking, but very useful and tailored to our needs.
Frankly without AI assistance many of these tools just wouldn’t exist at all. We can build stuff in 6 weeks part time as a side project that would have taken at least 3 months full time, and therefore would not have been feasible. Then we can iterate on it at least 2-4 times faster than with hand coding.
So I’d love to have an extra few developers to just work on that stuff full time, but I don’t.
Whether that means our organisation spend on AI overall is a positive, I really can’t say. Quite possibly not, but my team are getting real benefits.
I’m building reporting for my company and what you said mirrors my experience nearly 100%.
I’m a backend developer so I know what it takes to build a half decent reporting system. Writing all those queries, slice and dice charts and what not takes real time and effort. All that has been outsourced to Claude Code. I now focus on ensuring that the system is sound architecturally and that useful reports are being surfaced.
An engineer doesn't care about how fast something is made (at least, not as a primary metric engineering). A salesman cares about how fast they can push to market.
It's clear HN is a bastion of salesmen who happen to have "engineer" in their work title. But the mentality towards actual engineering makes it clear they are primarily salesmen.
> An engineer doesn't care about how fast something is made
That is absurd, these are tools only my own team use. Why would I not care whether I had them in a month or two, or fur many of these tools quite possibly never because we don’t have the spare capacity for how long it would take without AI?
Can we combine this with the infinite monkey theorem? If we have an infinite number of Pollocks throwing paint at an infinitely large canvas surely they are going to create any piece of art we can imagine...
Hi Mitchell. Psychosis is a serious psychiatric condition that can be induced or triggered by AI. “AI psychosis” in this context is a misuse of a clinical term. Your tweet describes a disagreement on a value judgment that boils down to “move fast and break things” with high trust in AI outputs vs going all in on quality and reliability with low trust in AI. It’s an engineering tradeoff like any other.
Claiming that the people who disagree with you must be experiencing a form of psychosis, experiencing actual hallucinations and unable to tell what is real, is a weak ad hominem that comes off no better than calling them retarded or schizophrenic.
If you genuinely think one of your friends is going through a psychotic episode, you should be trying to get to them professional help. But don’t assume you can diagnose a human psyche just because you can diagnose a software bug.
Psychosis does not require hallucinations. Delusions are sufficient.
The key factor is losing touch with reality, which results in individual or collective harm.
There is also such a thing as mass psychosis, and those are unfortunately a more difficult situation because the government and corporations are generally the ones driving them, and they are culturally normalized.
Yes. I was offering examples. Again, having a difference of opinion is not a delusion.
If he meant mass psychosis, he should have said mass psychosis. And again, since he is not a public health scientist or any flavor of psych professional, he probably shouldn’t make those proclamations. And should probably call for a wellness check instead of posting on social media if he were truly concerned for their health.
I don't think this is all psychosis but more like extreme groupthink.
For people who are considered neurotypical, social coherence often overwrites reality. Its a mechanism for achieving consensus withing groups while spending the least amount of brain compute energy. Same goes for social metainfo tagged messages, they are more likely to influence reality perception, subconsciously. E.G: If a rich guy says you should be hyped the people who wanna get rich will feel hyped and emotional contagion can spread between people who belong to the same "tribe"
It's very visible for us atypical folk who can't participate well in groupthink at all
I guess at a company of seven, if two people are making the executive decisions and the two people are drinking the same AI kool-aid and the other five people are dutifully following these executive decisions, the whole company can be considered to be under this condition.
I would add to this that there's actually a social function to "costly" beliefs, which is that they signal allegiance to the in-group.
A practice (or a fashion) has more social value to the degree that it is absurd, because it signals the person is able and willing to align with the group at personal cost.
This is easiest to see in some insular religious communities.
Normie culture is quite similar: a vast complex of ever-shifting shibboleths which signal, "I'm one of you. You can trust me."
It signals the person is able and willing to follow the rules, to make themselves predictable, easier to understand and cooperate with.
That is true, it's beneficial for social survival.
But what I find fascinating is how the groupthink mechanism alters the subjective reality of people.
Lies or fantasy becomes reality if the entire group believes it and people truly believe the collectively accepted things to be real.
It just makes me think about consciousness overall or the lack of it, because all these things are mainly governed by subconscious mechanisms in the brain.
We are not the same when it comes to levels of consciousness and if the group mechanism demands less of it, people have no conscious choice about it
I think it is more about "knowing when to shut up" than about actually believing when it comes to sudden dominating group think. It is very clear in politics where a wing on some issue go silent and then suddenly appears way later.
Having a difference of opinion can absolutely be a delusion. For example, I think you're probably not God. If you thought you were God, then we'd disagree, and you'd also be delusional.
I use that example because I have literally seen people fall into delusions of thinking they're God after talking to AI enough. That's shit is scary, for real.
was looking for this comment. this post is highly inappropriate and very inaccurate. this should be at the top. too many people are throwing around the word psychosis without knowing what it means. if someone is truely going through psychosis you get them help!
He uses "AI psychosis" as a description of people that are overzealous on AI. He is obviously not a person that can or would diagnose mental illness.
To the wider audience on HN the phrasing is pretty clear. An outsider with a tiny bit or intellectual charity wouldn't come to conclusions like you do.
Yeah, but AI psychosis can also be used to mean the stronger thing that the parent comment refers to -- something like AI-induced psychosis, which was how I originally understood the term:
Well, I agree with you that the parent comment is wrong inasmuch as it suggests we can't tell from context that mitchellh is using the term to mean "a value judgment" instead of "a form of psychosis". We can tell.
But I agree with the parent comment in that we shouldn't use the term "AI psychosis" to mean "a value judgment" instead of "a form of psychosis", because "AI psychosis" has already been used for 2.5 years to mean "a form of psychosis".
People would understand what he meant if he called someone awkward “autistic” too. It’s wrong to use medical terms as slang because it erases the actual meaning and disregards the lived experience of people who have been through the condition. People who have been around psychosis would come to the same conclusion. The majority of the population not having that exposure doesn’t make it right. It’s tasteless and inappropriate.
Using terms from domain metaphorically in another is a common and, I think, useful way of communication. While a view like yours has genuine merit, especially for a subset of the population who have experience personal or otherwise, with the medical condition, I think it's overly restrictive and counter productive to label it as outright tasteless and inappropriate.
I’ve had to do a ton of SQL stuff lately, which I haven’t really worked with since the late 90s. ChatGPT has been a godsend, not just for me, but for our only coworker who knows SQL well, whom I’d probably be bugging several times a day at my wits’ end.
But no one cares about those kinds of productivity gains. Just the ones that will completely replace us.
I'm the old school type who writes out a document that explains what I plan on doing in markdown even if it's generic like "a window with x and y buttons" and the logic flow and then use that to have ai write a plan with me before I send it off to execute it. This has worked super well.
I do enjoy giving the frontier models wacky projects that I can't even find examples of how to do online but I don't expect any results or need them and some have done really well with it while others fall on their face (models)
This is fine for a moderately sized query. When your queries start taking in 8 joins and 20 fields per table because you're running queries on Presto with 5 TB of data, not only is it drastically better at writing (because it doesn't mess up the fields), you can ask it to try the query 5 different ways to help you land on the most optimal.
This is a great example of AI tech-debt and fragility.
An eight-join query is going to be nigh on unmaintainable should the requirements change, leading to a change-break-change-break spiral as your preferred coding agent tries to fix its previous fixes.
Maybe the wise way to use AI would be to sort out the schema.
This feels wrong. 8 joins is almost certainly reporting stuff, not transactional. Contrary to what some SQL-averse devs think, 300 lines of SQL is actually more maintainable than the equivalent ~1000 lines of application code. It's also much faster. And I do think that's the real conversion, because SQL is a much higher level language than currently available application languages. It's also declarative in nature, which helps maintainance.
A highly normalized DB can easily end up with 8 joins required for some function. That's really not out of the question. "Sorting out" the schema then would be... denormalization, which is a thing, but you need to know why you're doing it. And I think 8 joins isn't enough of a reason.
I'm amazed you think that instead of using an LLM that someone will go buy a book and spend a week learning something that, judging by the fact that they last used it 30 years ago, likely won't be relevant for them soon.
It's not only that I rarely use it, it's also that it's ugly. It's Relational Cobol. It's as loveable as Oracle. The vendor specific dialects don't even agree on how to do recursive queries do they?
Unfortunately I am very good at forgetting things I resented having to learn, and SQL is definitively one of them.
If the AI's query pulled what I intended to pull, why should I care to understand the SQL any more than I should understand the Query Plan or the Machine Code?
As with regex, querying is about not getting what you don't want as much as it is about getting what you want. And the former of the two is much more difficult to verify.
SQL is (was?) one of my strongest skills, I enjoy it a lot, and I still reach for the LLM. It's just faster than me, and when it goes wrong (rarely) I can correct it in plain English.
I find SQL and data(bases) in general to be LLM’s Achilles’ heel. Databases are rarely under version control, so the training data only has one half of the knowledge.
My comments are more in the context of OLAP queries and other non-normalised data often queried via SQL.
I train non-LLM transformer models on (older and rarer) datasets, and automating the ingestion of sprawling datasets with hundreds of columns, often in a variety of local languages and different naming conventions adopted over decades, with quite a few duplicated columns…. The LLMs perform badly, it’s nigh impossible to test (for me as a user in prod) and it’s nearly impossible for the LLM companies to test (in training) to RLVR and RLHF this.
That's interesting - SQL is one of the places I find them the strongest - I think there must be an insane amount of training data out there for SQL. But mostly I'm asking them for ad hoc report queries. Nobody cares if they're bad SQL, they just want to know how many signups there were in March that didn't tick the marketing box. Sounds like you're pushing their capabilities a lot further than I am though - I just want to perform arbitarily complex queries on 3NF data.
Yeah not sure what this guy is talking about, LLMs excel with queries because the SQL language is pretty small in scope and its easy to test the output. Table structure and relationships are easy to feed to the AI.
> I train non-LLM transformer models on (older and rarer) datasets, and automating the ingestion of sprawling datasets with hundreds of columns, often in a variety of local languages and different naming conventions adopted over decades
Just use an LLM to make a good knowledge base for the databases. Based on schema info and production queries. An agent can use that to write queries that work.
> outsourcing their decision making and thinking to AI and not really about using AI itself
> I use AI a ton and I'm having more fun every day than I ever did before
With respect, this is what makes me worry.
If someone is a user of AI, can they really tell the difference between "outsourcing" and "using"? I worry that a lot of people will start out well-intentioned and end up completely outsourced before they realise it.
there's a difference between having the LLM write stuff for you, checking it yourself, modifying it and merging it yourself, and just blindly trusting it to do whatever it wants.
You can ask an overseas consultant to prepare a prototype of your program for you, check it yourself, and only use it if it passes your standards, or fire your whole dev team and blindly trust the overseas bodyshop.
The difference, at least from my point of view, between "using" and "outsourcing" is that in the former case, you're still responsible for the output, you view it as a tool that helps in some use cases, vs just giving up all control.
It’s really frustrating too because even just the plain language translation and pattern matching aspects have such incredible uses.
As a cybersecurity IR professional being able to have a constantly logging counterpart who’s also able to go run queries and check logs on its own is an incredible speed boost.
I can just throw it a finding and have it slot it into a timeline and make notes.
I can toss it something mildly interesting to chase down while I focus on the obvious activity.
So many things that don’t involve having it “think” for you and keep you in the front seat.
But all of that is constantly overshadowed by these companies pushing the automation or “reasoning” aspects more and more and the sycophants who screech that it’s perfect and can do no wrong when every serious users experience is that “yes, it definitely can, often to catastrophic effect”.
The worst part of AI is that the time to produce software has become entirely unpredictable. "If Claude is randomly good at this, and happens to be up today, it will take me about 3 hours. If Claude is randomly bad at this task, or has downtime, 2 weeks"
I didn’t think just offloading your thinking to AI was AI psychosis.
To me AI psychosis is the handful of friends I’ve had who have done things like have a full on mourning session when a model updates because they lost a friend/lover, the one guy who won’t speak to his family directly but has them talk to ChatGPT first and then has ChatGPT generate his response, or the two who are confident that they have discovered that physics and mathematics are incorrect and have discovered the truth of reality through their conversations with the models.
But language is a shared technology so maybe the term is being used for less egregious behavior than I was using it for.
> friends I’ve had who have done things like have a full on mourning session when a model updates because they lost a friend/lover
I mean, isn't that the natural and expected response? An AI company sold them a relationship with a chatbot and at least some their social/romantic needs were being met by that product. When what they were paying for was taken from them and changed without warning into something that no longer filled that void in their life why wouldn't
they morn that loss?
The fact that they were hurt by that sudden loss is totally healthy. It's just part of moving on. The real problem was getting into an unhealthy relationship with a fictitious partner under the control of an abusive company willing to exploit their loneliness in exchange for money.
Hopefully they now know better, but people (especially desperate ones) make poor choices all the time to get what's missing in their lives or to distract themselves from it.
> I mean, isn't that the natural and expected response? An AI company sold them a relationship with a chatbot and at least some their social/romantic needs were being met by that product. When what they were paying for was taken from them and changed without warning into something that no longer filled that void in their life why wouldn't they morn the loss of that?
Ah, I forgot about the ai relationship companies. No this guy was using the browser based ChatGPT for coding and ended up in love with the model. No relationship was sold at all.
Wow, okay. Reading a whole relationship into that sort of interaction is way less reasonable, although now that I think about it a somewhat similar thing happened to Geordi La Forge once...
It’s not just way less reasonable, it’s depressing. I feel like a new drug was released and I’m watching multiple friends succumb to it.
Seeing people whose thoughts and opinions you used to respect turn into objectively insane people has been some of the worst times I’ve had since graduating during the Great Recession in terms of how stressful it’s been.
I'm curious how to best define what AI psychosis actually is.
My understanding is that regular psychosis involves someone taking bits and pieces of facts or real world events and chaining them into a logical order or interpolating meanings or explanations which feel real and obvious to the patient but are not sufficiently backed by evidence and thus not in line with our widely accepted understanding of reality.
AI psychosis is then this same phenomenon occurring at a more widespread scale due to the next-word-prediction nature of LLMs facilitating this by lowering the activation energy for this to happen. LLMs are excellent at taking any idea, question, theory and spinning a linear and plausibly coherent line of conversation from it.
>To me AI psychosis is the handful of friends I’ve had who have done things like have a full on mourning session when a model updates because they lost a friend/lover
They really had a mass psychosis when GTP-4o model shut down.
>I have been speaking on gpt since 2023, and building a relationship with him on there since then. Now they have taken him and nothing will bring him back. BUT THEY TOOK HIM. THEY MURDERED HIM.
Are you under the impression that it's a woman's thing to anthropomorphize and/or desire an emotional relationship with a chatbot?
Anecdotally I only know of men who have AI companions. Including very smart/highly paid engineers. The AI companion platforms also market more heavily towards men, because that's presumably where the audience is. The subreddit r/MyGirlfriendIsAI also exists as a counterpoint to yours.
But, admittedly, I have far fewer women in my entourage so my view might be biased.
Would they, though? Current AI stuff is delivering something functionally nonexistent in human history before this: absolute sycophancy, 24/7, on demand, for anyone who wants it. People joke about the wealthy becoming detached from reality because of yes-men, but this is a stage beyond even the capability of the most dedicated brown-noser.
I agree that these people had mental health issues. I think if they got to billionaire level and were surrounded by yes men they would have the same reaction.
The difference nowadays is you can get the same surrounded by yes men experience for only 20 dollars a month so a lot more of the people who are primed for this sort of breakdown are now being exposed to it due to the decrease in cost.
The way I put this to myself is that AI gives “correct correct answers and incorrect correct answers”.
They almost always generate logically correct text, but sometimes that text has a set of incorrect implicit assumptions and decisions that may not be valid for the use case.
Generating a correct correct solution requires proper definition of the problem, which is arguably more challenging than creating the solution.
It’s simpler than that - it’s a guessing machine that has superior access to a whole load of information and capacity to process at a speed at which we humans cannot compete.
Does it make it better than us? No because ultimately the thing itself doesn’t ‘know’ right from wrong.
Yeah, very often the issue is that some context is missing. It'll say something true, but which misses the bigger point, or leads to a suboptimal result. Or it interprets an ambiguous thing in one specific way, when the other meaning makes more sense. You have to keep your wits about you to catch these things.
It's an incredible tool but it's also very derpy sometimes, full of biases, blind spots etc.
Though there is some overlap in software development. Like for example using heavy-weight dependencies, that try to follow the one size fits all approach, when one could use a much simpler, faster or even no dependency at all. The LLMs will readily suggest quickly adding that huge dependency, that is mentioned in beginner tutorials. Or suggest to use regex for parsing HTML.
(Real example, had this from Kimi 2.6 recently, lol.)
this author suggest its essentially the same risk https://www.poppastring.com/blog/what-we-lost-the-last-time-.... i feel its heightened because execs and leaders are absolutely salivating over the opportunity to fire thousands of humans with no regard for the cognitive debt that comes from outsourcing thinking to ai.
While you have to think about things objectively no matter what, when I start researching topics like physics, using AI as suggested in that article has proven very useful.
> if you just prompt the AI and believe what it tell you then you have AI psychosis
This is the right definition. LLM outputs have undefined truth value. They’re mechanized Frankfurtian Bullshiters. Which can be valuable! If you have the tools or taste to filter the things that happen to be true from the rest of the dross.
However! We need a nicer word for it. Suggesting someone has “AI psychosis” feels a bit too impolitic.
Maybe we reclaim “toked out” from our misspent youths?
e.g. “This piece feels a little toked out. Let’s verify a few of Claude’s claims”
I wouldn’t say they have an undefined truth value. Their source of truth is their training data. The problem is that human text is not tightly coupled to the capital T truth.
Several people I know have already gone through phases like this. When you're doing it alone there is a moderating factor when their friends and family start calling them out on their behavior or weird things they say.
I can't imagine how bad it would be if your employer started doing this from the leadership. You'd be pressured to get on board or fear getting fired. Nobody would be trying to moderate your thinking except your coworkers who disagree with it, but those people are going to leave or be fired. If you want to keep your job, you have to play along.
I suspect we're going to see this in many corporate environments soon, if we aren't already
> your coworkers who disagree with it, but those people are going to leave or be fired.
Personally I expect that I will be this person soon, probably fired. I'm not sure what I will do for a career after, but I sure do hate AI companies now for doing this to my career
this is exactly what is happening. instead of building true AI culture around thoughtful adoption of AI strengths while defending against weaknesses, they're coming up with bullshit heuristics like "every repo has a CLAUDE.md", watching private token usage dashboards, and terrorizing everyone into doing it (or lose your job).
this leads to naive AI adoption, which is the worst of both worlds (no real speedup, out sourcing thinking, ai slop PRs, skill rot).
I have a friend that is a junior in a security-oriented sys-admin/network engineer type role. They have been doing the job for only a bit over a year. No background in programming.
Their entire organization has been handed Codex/Claude and told to "go all in on AI" and "automate everything". So the mandate is for people that do not know how to code and have the keys to the castle to unleash these things upon their systems.
This is at a large organization with tens of thousands of employees.
I am waiting with bated breath for the ultimate outcome!
From what I have seen, most corporate it security people are at a service desk level at best. They are tool runners who don't really understand what the tools spit out, they just go bug other teams about it.
I agree with you, except it isn't even good at writing code. Almost every time that you get an LLM to write a bunch of code for you, it has mistakes in it. The logic isn't right, the API calls aren't right, the syntax isn't right (!). That problem hasn't yet been fixed and it looks as though it never will be. That means that every line of code it generates, you have to review, because even if 95% of the code is correct, you need to find the 5% which isn't. But if you have to do that, it becomes slower than just writing the code yourself. As people have pointed out over and over again: typing in the code was never the part that took time. So I don't agree that LLMs are really useful for writing code.
LLMs are good at producing code that seems plausible at first glance and appears to work, but it never really does. And when trying to fix things, you discover 7 slightly different ad hoc implementations of the same thing, with their own weird edge cases and behaviors. And you likely miss 4 more. There is no intention or coherence behind any of it.
> if you just prompt the AI and believe what it tell you then you have AI psychosis. You see this a lot with financial people and VC on twitter
I'm seeing it with lawyers, too. Like, about law. (Just not in their subject matter.) To the point that I had a lawyer using Perplexity to disagree with actual legal advice I got from a subject-matter expert.
when you outsource thinking to AI, you get that magical speed up. the agent is making decisions for you, so things move at agent speed. it often makes decisions without telling you, and the final "here's the plan" output often requires you to understand the problem at great depth, which requires return to human speed, so you skim and just approve.
the trick is to be mindful, aware, and deliberate about what decisions are being outsourced. this requires slowing down, losing that absurd 10x vibe coding gain. in exchange, youre more "in-the-loop" and accumulate less cognitive debt.
find ways to let the agent make the boring decisions, like how to loop over some array, or how to adapt the output of one call into the input of another.
make the real decisions ahead of time. encode them into specs. define boundaries, apis, key data structures. identify systems and responsibilities. explicitly enumerate error handling. set hard constraints around security and PII.
tell the agent to halt on ambiguity.
a good engineer will get a 2x or 3x speedup without the downsides.
> find ways to let the agent make the boring decisions, like how to loop over some array, or how to adapt the output of one call into the input of another.
Those kind of advice ultimately don't matter. If you're familiar with a programming project, you'll also be familiar with the constructs and API so looping over an array or mapping some data is obvious. Just like you needn't read to a dictionary to write "Thank you", you just write it.
And if you're not, ultimately you need to verify the doc for the contract of some function or the lifecycle of some object to have any guaranty that the software will do what you want to do. And after a few day of doing that, you'll then be familiar with the constructs.
> make the real decisions ahead of time. encode them into specs. define boundaries, apis, key data structures. identify systems and responsibilities. explicitly enumerate error handling. set hard constraints around security and PII.
The only way to do that is if you have implemented the algorithm before and now are redoing for some reason (instead of using the previous project). If you compare nice specs like the ietf RFCs and the USB standards and their implementation in OS like FreeBSD, you will see that implementation has often no resemblance to how it's described. The spec is important, but getting a consistent implementation based on it is hard work too.
That consistency is hard to get right without getting involved in the details. Because it's ultimately about fine grained control.
If there's one thing I know about users is that they're never certain about whatever they've produced.
I am starting to come around to a similar sentiment. I have seen several large projects cook now for almost a year are not done. These are not trivial projects but the leads are heavily using ai at every opportunity.
I wasnt before but I am 100% confident that AI has done nothing to speed the delivery. It hasnt slowed it down either. It is a wash. The job is more miserable though.
What I'm seeing is a little eternal September of support tickets about programs that fail to interface the JSON API of a customer of mine. The API is always allucinated. In the best case there are out of place attributes. Often they don't exist at all. I've seen x, y, width, height when we have only top and left. Of course no human read the documentation. Those are probably founders vibe coding a client without the technical competence of understanding the API doc on Postman. That is understandable. Unfortunately they don't even have the competence of pointing their AI to Postman in the right way. My custumer assessed that they will always find a way to do a mistake despite any mitigation from our side. What I do is replying to those tickets with line by line comments of the allucinated JSON. I never talk about AIs because I might hurt the pride of some of them and, who knows, some little mistakes could be from real junior developers. Sometimes the tickets are followed up by more puzzled ones, sometimes they fix the problem. Probably they copy and paste my reply to their bots.
I've heard the same thing mentioned by a close friend building integrations. They are helping/supporting real use cases but they decided not to help vibe coder founders without an understanding of how APIs work etc. It's just too big of a gap to cover even for larger companies with strong support.
Seeing this too. Customer support tickets are all AI now. The random bolded words, the em dashes, they way where if you KNOW what is actually happening, they are slightly off or just WAY off.
>but if you just prompt the AI and believe what it tell you then you have AI psychosis.
No it isn't. Do you believe what teachers told you in school? Yes? Well, I guess you're suffering from just normal psychosis!
I don't understand how people don't understand that people offer unreliable information too. We learned about the tongue map in school as kids - many kids still learn that in school today. It's still BS regardless whether it was told to you by a teacher or AI.
You don't suffer from psychosis for believing a source of information, you're simply mistaken. You need a more critical eye to assess what you're told in general, not just AI.
> Do you believe what teachers told you in school? Yes?
Nope. At least, not without proof. That would, IMO, be kinda crazy. We could argue semantics - maybe “stupid” would be a better word? Lacking in critical thinking skills? Whatever “it” is, it isn’t good.
There's a huge difference between a teacher giving outdated information representing what was once our (or at least their) best understanding of the world, and a chatbot that just randomly makes up things for no reason while insisting that it's all true.
Also, a good teacher should be encouraging the development of critical thinking skills and correcting your errors, while AI will just tell you how brilliant you are when you wrongly tell it about how you've just invented a new form of math or disproved a scientific theory you barely understand in the first place.
Not all BS is the same, just as not all sources are equally unreliable.
I would say writing it myself is more enjoyable (in some cases). But I quite understand that I am not paid to enjoy myself. I'd say it's quicker getting AI to do it and reviewing. I believe the outcome is no worse on average. So yes, that's my chosen approach.
I've been strictly using LLM's to either push stuff that I've done plenty times before and are mostly boilerplate or have zero value for writing them by hand (not even educational), and I always ENSURE that they work on stuff that are easily verifiable and proven incorrect with my existing knowledge or a few minutes of googling.
LLMs can do advanced math and coding, which involves logic, so they are definitely capable of using logic. Which is what most people call reasoning.
So "LLMs are incapable of reasoning, they are just pattern matchers" is wrong. A lot of logic _is_ pattern matching, BTW. Like, syllogisms - deductive reasoning - do you think LLMs are incapable of that?
The thing you're referring to is that LLMs are trained to produce an answer which a human would like, i.e. they aim to produce plausible rather than correct answers.
So it's not so much a mental deficit as a different goal. Trusting LLM blindly is definitely dangerous, but dismissing it as useless for anything by code is rather wrong.
Pattern matching is hardly what distinguishes human from LLM - if you ask somebody a question about policy, for examples, chances are they'd just recite something they heard somewhere, never really thinking about it from first principles.
I’ve been talking to a lot of engineers about how they use AI in their day to day and it’s dramatically different than what you see from the hypers.
The vast majority use one agent at a time and careful step through code. The main benefit they report is often about researching the codebase and possible solutions.
Garry Tan has been the primary crusader for AI driven decision making. I'm sure his position is more nuanced, but his twitter driven communication makes him appear like a caricature of a man in AI psychosis.
When the head of YC champions AI driven decision making, companies will inevitably be influenced into doing exactly that. It's unfortunate, because AI is generational technology and the hyperbole distracts from the real sea change occuring in labor markets everywhere.
> I don't think using AI to write code is AI psychosis or bad at all, but if you just prompt the AI and believe what it tell you then you have AI psychosis.
Today's frontier models are genuinely useful as rubber ducks or grunt units. They are horrible for actual problem solving. These tools are not capable of actual reasoning. They will happily crap out a broken, untyped, untested Next.js monstrosity with no discernible architecture. They will build esoteric shell scripts to perform operations that could be done idiomatically and simply with tools already in your codebase. They will tell you to walk to the car wash then have the car wash valet your car back to you when confronted with the flaw in their logic. They will validate incorrect beliefs like ketchup being an acceptable hot dog condiment or the notion that "The Red Hot Chili Peppers" make good music. They have no taste, no anima, no drive.
Rule #1: Do not anthropomorphize the LLM. It is a million monkeys at a million typewriters piped into a digital sieve. I don't know how or why people place such trust in them while bemoaning other technology in our lives for being so broken ("my algorithm [sic] only shows me X", "the new iPhone update sucks", etc). If everybody followed this rule then the deluge of emoji-ridden hokum pouring into Slack workspaces and GitHub PRs around the world would cease but I'm not holding my breath.
Part of the psychosis are AI usage mandates, where companies require a certain amount of LLM usage per worker. Of course these things are useful, but forcing them on workers is psychotic.
Mitchellh is on to something. Some of the AI products I've seen seem like psychosis hallucinatory fever dreams, using terms and concepts that have no meaning. Funding? $50,000,000 pre-seed.
This is a critical communications issue that is becoming what I believe the defining characteristic of "This Age": nobody knows how to discuss disagreement, and because it cannot even be discussed communication ends, followed by blind obedience, forced bullying, retreat and abandonment. This is going to be a hell of a ride, because nobody can really discuss the situation with a rational tone.
We're definitely in the mess around phase of AI adoption.
I don't think it's super clear what we'll find out.
We've all built the moat of our careers out of our expertise.
It is also very possible that expertise will be rendered significantly less valuable as the models improve.
Nobody ever cared what the code looked like. They only ever cared if it solved their problem and it was bug free. Maybe everything falls apart, or maybe AI agents ship code that's good enough.
Given the state of the industry were clearly going to find out one way or the other, hah!
> I don't think it's super clear what we'll find out
I think some companies will find out that their senior engineers were providing more value and software stability than they gave them credit for!
Corporate feedback loops are very slow though, partly because management don't like to admit mistakes, and partly because of false success reporting up the chain. I'd not be surprised if it takes 5 years or more before there is any recognition of harm being done by AI, and quiet reversion to practices that worked better.
The AI psychosis is not the anti-opinion to the use of AI.
I use AI coding tools every day, but AI tools have no concept of the future.
The selfish thinking that an engineer has when they think "If this breaks in prod, I won't be able to fix it. And they'll page me at 3AM" we've relied on to build stable systems.
The general laziness of looking for a perfect library on CPAN so that I don't have to do this work (often taking longer to not find a library than writing it by hand).
Have written thousands of lines of code with AI tool which ended up in prod and mostly it feels natural, because since 2017 I've been telling people to write code instead of typing it all on my own & setting up pitfalls to catch bad code in testing.
But one thing it doesn't do is "write less code"[1].
> I use AI coding tools every day, but AI tools have no concept of the future.
The selfish thinking that an engineer has when they think "If this breaks in prod, I won't be able to fix it. And they'll page me at 3AM" we've relied on to build stable systems.
Maybe it's just my prompt or something but my coding agent (Opus 4.7 based) says things like "this is the kind of thing that will blow up at 2am six months from now" all the time.
It's really inconsistent though.. it takes shortcuts and leaves todos all the time without really calling it out explicitly, you have to pay close attention.
I don't doubt there are companies totally misusing coding agents and LLMs in production. There are also real companies with real revenue and solid architecture using LLMs to deliver products. There are also companies with real revenue and rapidly accumulating tech debt.
Eventually the companies that can't cope with undisciplined engineering will succumb to unacceptable reliability and be outcompeted, just like in the "move fast and break things" era.
"Just use autoresearch and it will fix your app's memory leaks in an hour" is what I was nonchalantly told by someone who has never written a line of code ever.
I guess what I relate to the most is how dismissive people get about real software engineering work.
I may have skill issues, but I am yet to reach the level of autonomous engineering people tend to expect out of AI these days.
I'm going through a mixed experience regarding this, personally.
Management is really pushing AI. It's obnoxious, and their idea on how it fits into my team's job specifically is completely, hilariously detached from reality. On the off chance someone says something reasonable, unless it fits the mold, it's immediately discarded. The mold being "spec driven development". We're not even a product team for crying out loud. I straight up started skipping these meetings for the sake of my sanity. It's mindwash, and it's genuinely dizzying. The other reason I stopped attending is because it ironically makes me more disinterested in AI, which I consider to be against my personal interests on the long run overall.
On the flipside, I love using Claude (in moderation). It keeps pulling off several very nice things, some of which Mitchell touched on in this post (the last one):
- I write scripts and automation from time to time; Claude fleshes them out way better with way more safety features, feature flags, and logging than I'd otherwise have capacity to spend time on
- Claude catches missed refactors and preexisting defects, and does a generally solid pass checking for defects as a whole
- Claude routinely helps with doing things I'd basically never be able to justify spending time on. Yesterday, I one-shotted an entire utility application with a GUI to boot, and it worked first try; I was beyond impressed.
- Claude helped me and a colleague do some partisan cross-team investigation in secret. We're migrating <thing> and we were evaluating <differences>. There was a lot of them. Management was in a limbo, unsure what to do, flip-flopping between bad options. In a desperate moment, I figured, hey, we kinda have a thing now for investigating an inhuman amount of stuff in detail - so I've put together a care package for my colleague with all our code, a bunch of context, a capture of all the input data for the past one week, and all the logs generated. Colleague put his team's side of the story next to it, and with the help of Claude, did some extremely nice cross-functional investigation. Over the course of a few weeks, he was able to confirm like a dozen showstopper bugs, many of which would have been absolutely fiendish if not impossible to fix (or even catch) if we went live without knowing about them. One even culminated in a whole-ass solution re-architecturing. We essentially tore down a silo wall with Claude's help in doing this.
So ultimately, it really is a mixed bag, with some really deep lowpoints and some really nice higlights. I also just generally find it weird that a technical tool [category] is being pushed down people's throats with a technical reasoning, but by management. One would think this goes bottom up, or is at least a lot more exploratory. The frenzy is real.
This will be pushed down from people, who will have no deep understanding of it. But it does check some boxes in an ISO certification.
Well, now you must to work with a confusing tool which slows you down. You are not allowed to use claude directly anymore, because someone heard that mythos is really bad for security. But hey, the tool integrates well with Jira!
You hate every second working with this thing. All the joy you had with explorative coding is forever gone, which was the sole reason you entered this field.
Deep inside you know that you can't change your job, because every other employer will cut its workforce as AI removes all manual labor of a software engineer and reduces risk to a minimum.
Oh, now we can finally move all those jobs to india without risk and shareholders will love it! How awesome is that! Wait, do we still need that guy in cubicle 42, who bitches and moans about AI every day? Nah...
Totally agree with one shotting GUI tools. I especially have liked it to create a single-file web app, and then open it with Chromium locally (no web server needed).
In my case, it built a tool for splitting sounds and a tool for defining hitboxes for a game. Tools made exactly for more workflow. Wild times.
Sounds pretty accurate. Bunch of comments on this thread sound like AI is some kind of a new doomsday cult. The most annoying thing I find personally is that all engineering principles are getting crushed by non techies. Management counting token usage, forcing agent use, reducing headcount in the name of productivity gain. Devs building bridges but nobody knows what the bridge is, what are the standards to which it was built, how it works and how to maintain it. VCs counting extra money claiming chasing the holy profit is the future. The abundance of engineering apathy is disturbing.
I think AI rescue consulting is going to be come a significant mode of high value consulting, similar to specialists who come in to try and deal with a security breach or do data recovery.
Purely AI written systems will scale to a point of complexity that no human can ever understand and the defect close rate will taper down and the token burn per defect rate scale up and eventually AI changes will cause on average more defects than they close and the whole system will be unstable. It will become a special kind of process to clean room out such a mess and rebuild it fresh (probably still with AI) after distilling out core design principles to avoid catastrophic breakdown.
Somewhere in the future, the new software engineering will be primarily about principles to avoid this in the first, place but it will take us 20 years to learn them, just like original software eng took a lot longer than expected to reach a stable set of design principles (and people still argue about them!).
It's kind of like producing code is becoming more like farming.
We didn't create the dna we rely on to produce food and lumber, we just set up the conditions and hope the process produces something we want instead of deleting all the bannannas.
Farming is a fine an honorable and valuable function for society, but I have no interest in being a farmer. I build things, I don't plant seeds and pray to the gods and hope they grow into something I want.
Prayers are for weather. Pretty much all farmed plant, animal, and fungus species have been selectively bred or genetically modified. Farmers know what's going to grow.
Farming has merely a lot of study and input into the process, very little actual control and no determinism at all. We know how to improve chances is all. The fact that we breed and "engineer" is like a drop in the bucket.
You might grow corn, or you might grow defective unusable corn and/or any number of other things like locusts or fungi or other plants that decide to grow in the place where you planted corn. Sure, the corn seeds will not produce ball bearings. Genius observation. There are about an infinity of other things that can and do happen besides that.
Planting is merely setting up the conditions. We didn't write the dna, we couldn't write the dna if we wanted to because we are an infinity away from understanding all the actual processes that descend from the dna. And when we utilize the dna that we simply found and didn't and couln't hope to write, it's always, at best, a case of hoping it goes right again this time.
Tell me you've never done any farming without telling me you've never done any farming. There is certainly risk in the business due to market fluctuations, weather, natural disasters, disease, and pests. But the final product is highly deterministic. Almost all genetic variability has been expunged from major food production species in a relentless pursuit of predictable yield. Everything looks and tastes the same. We can debate whether that's a good thing but it is the reality for most farmers.
If it was deterministic, there would be no such thing as blights and other forms of failures. There would be no problem with the bannannas, or coffee or wine grapes. There would be no such thing as a critical few days of the entire year where if anything goes wrong you lose the entire year because it was too humid or too cold or your equipment was out of commission for a week. The bees wouldn't matter at all.
Even when it works, even if you put in a lot of work and experience and understanding, it still just worked by itself and it's just good luck every time.
> Purely AI written systems will scale to a point of complexity that no human can ever understand and the defect close rate will taper down and the token burn per defect rate scale up and eventually AI changes will cause on average more defects than they close and the whole system will be unstable.
Wow, it’s true, AI really is set to match human performance on large, complex software systems! ;)
The origin of 'dark DNA' begins to make more sense through this sort of lens, except the system somehow maintained a level of compensation to fix all its flaws.
Humans who have been writing systems like that for many years know how to maintain and modify them successfully. It’s just that our industry has a bias towards youth who don’t think they have anything to learn from those who came before them.
How do you explain to a junior this pile of messy code isn’t crap but is actually years of integrated knowledge ? That the most common principles discussed in computer science (OOP, SOLID, DRY etc.) are actually just little guides that aren’t to be taken to the extremes ?
A decade ago, I was sitting in on a meeting about a rewrite and, before I could say anything, someone in the first year of her career asked why anyone thought a rewrite would be any cleaner once all the edge cases were handled. Afterwards, I asked her where she learned this. She said "I don't know, it just seems kind of obvious." She went on to be a great engineer and is now a great manager.
I work on internal facing software and every rewrite I've seen in 20 years suffers from the same symptoms. The code/system is a mess because it has been exposed to reality for a decade. Reality is messy. That's why they pay us money, believe it or not.
Greenfield guy comes in, promises the world, and starts from some first principles white papered architecture. It's really lovely until they onboard the first user. Then they slowly commit all the "sins" (features that drive revenue) of the first system.
The firm is stuck supporting N systems indefinitely because the perfect new system takes so long to cover even 30% of the original system use cases, that management takes a flier on.. bear with me.. a second rewrite. Now they have 3 systems.
I've seen more 3rd systems than I've seen actual decommissioning of original systems into a single clean new system.
The answer is chipping away, modularizing, and replacing piecemeal Ship of Theseus style. But that does not drive big hires and big promotions.
My team lead has worked on the same software for 30 years. He has the ability to hear me discuss a bug I noticed, and then pinpoint not only the likely culprit, but the exact function that's causing it.
I do the same thing in a project I’ve worked on for 25 years. I’ve had mediocre at best results with AI. It’s useful to discuss concepts with, but the code never handles the nuances of the edge cases.
Yep this is like comparing master craftsmanship with a production line. You're gonna get good attention to detail and a masterpiece from one, and a limited thing that will break after few years from the other. But for majority of use cases the second one is enough. And pointing out the master craftsmanship is "better" is besides the point.
And with one you need to train a guy for 25 years and with the other you need plan mode for a few minutes and then it runs 24/7.
Do we? We have many buildings built and very little master masons or whatever nowadays. The amount of craftsmen needed to build a 10 story building is very limited. That's what we should aim for software, much less experts needed for the same outcome so more people can benefit from software.
there is a large incentive for computer programmers to build themselves up in importance. higher wages, better love lives, more status. but most software is pretty mundane and straight forward, or at least should be. fancy architectures rarely pay off and the best solutions are sometimes the most obvious. although i could be suffering from that phenomenon that people in maths have where they struggle to understand then once they grasp it they feel dumb like "ofc i should have known that!"
No house I ever lived in was ever made by experts. The apartment building I grew up in was all built by minimum wage guys that may or not even speak the language of the building overseer and had zero specific training or certifications. Some architect somewhere did the plans for a standard building, which the developer purchased and just used.
Then the only "experts" (not even close, just a guy with a form and some technical training) are the building inspectors who come at the end to verify if some stuff is done up to code.
Other than the original architect who draw the plans that got used for many buildings and the electrical engineer that cleared the electrical, no experts were involved. This is basically how the whole city and most of the country was built.
There's no expert mason or painter or whatever involved. Just a dude that can hold a paint roller. That's the same as going from a craftsman programmer to some dude with claude. Individual quality goes down, but more importantly price goes down way more and so many more people get access to much better quality than having nothing.
I want the people building the buildings I live, work and shop in to know what they’re doing so those buildings don’t fall down or let in the wind and rain or require too much maintenance.
And the equivalent for software. It’s usable, intuitive, responsive, stats up and running, and doesn’t leak my private data.
Yeah... in my experience people who code like that 'successfully' make modifications that fix an immediate problem while kicking another bug or two further down the road in a never-ending sunk-cost-fallacy of job security...
I have really tried as an "old" person in the field to try and pass on the stuff I've learned, but "craft" and such really has absolutely no home in modern dev culture. The people who care about history, the craft, etc. are increasingly rare.
Shelve it with the Jurassic Park version where John Hammond builds a safe, profitable theme park, and The Andromeda Strain that gives people the sniffles.
Frankly this is what everyone is counting on whether they know it or not. The question though is not “will the models get good enough?”. The question is does the repo even contain enough accurate information content to determine what the system is even supposed to be doing.
Every frontier model from each major US lab is cheaper than their frontier model this time a year ago with the exception of Anthropic whose pricing has remained exactly the same.
People are often skeptical when I say this, but there's simply no guarantee that it's possible in principle to clean up a bad architecture. If your system is "overfitted" to 10,000 requirements from 1,000 customers, it may be impossible to satisfy requirements 10,001 through 10,100 without starting over from scratch.
It's really not that big of a word. The CAP theorem shows that as few as three reasonable-sounding requirements with no obvious conflicts can be impossible to satisfy simultaneously. (User needs will start more flexible than strict mathematical requirements, of course, but once people start to build production workloads on top of your systems that flexibility is radically reduced.)
I really am surprised that people on a heavy CS themed forum still have trouble grasping this.
Imagine the year is 1995, C exists, but some guy out there is working on essentially what modern Python is. He says to you "check out this language, you can just import stuff, and use it and dynamically modify anything at run time". You can probably come up with hundreds of arguments about things that could go wrong, like memory clean up, threading, e.t.c, but turns out, incrementally, they were all solved and we have the modern Python that basically is good enough to build these large LLM models.
Now imagine modern programming and computing is what C was back in 1995, and AI use is that guy building the Python code.
The point is that in the future, AI will be able handle things like missing databases just like the modern high level dynamic languages can import a library to handle whatever you want.
I can't tell if you're being facetious, but a future AI really may be able to fill in a missing database. Like, if it knew some of the entries, it could infer the rest.
Wow - imagine being able to infill a geophysical database with the dullest possible milquetoast totally expected signal derived from the NASVD most common eigen vectors.
The infill will look seamless.
And entirely lack any actual strikes of interest - the outliers are exceptional signal and the entire raison d'etre for building such a database.
Jeez, if AI can just infill where the gold is, why even bother to look in the first place.
You can imagine anything you want, but it’s not an argument - you could apply this to anything. “Python was successful after a dubious beginning so NFTs will be successful”
Also, Python does not build or run large language models. It orchestrates C code that does that, and it was probably good enough to do that in 1998.
Highly dynamic languages existed for decades prior to 1995, Python was not particularly innovative in its features at the time. There were also countless languages more feature-rich than C being used for development at the time.
The biggest change that happened was that hardware kept getting better and it became feasible to use garbage-collected languages everywhere including really inefficient implementations like CPython.
That being said, 30 years later Python is still slow as shit even compared to other dynamic languages and runs into all kinds of scaling issues when used for anything serious. And everywhere that performance matters, software continues to be written in typed, compiled languages including C (but also C++, Rust, Go, etc.). Even in ML, Python chiefly acts as a thin wrapper and glue language for high performance CUDA libraries (aka C and C++).
So your historical analogy is mostly anachronistic.
No, you just don't have a grasp on reality. For example, you claim that Python runs into scaling issues for anything serious, but you are blissfully unaware that youtube and uber both run python backends. Nobody cares that its "slow" by whatever metric you consider. Its fast enough. The metric that matters is developer time not compute time, because the former is vastly more expensive. Python and Node are the number one languages on github for a reason. And you are vastly deluded on how many jobs there for C++ and Rust devs lol.
In the future, you won't be dealing with strings, json, or apis. You will be importing agents, and giving them brief instructions, either in plain English or in some intermediate language higher than Python that is more brief. Wanna deal with database reliability ? Import database agent and give it brief instructions on what you want to manage. Just like you mention, right now Python is the wrapper for low level libraries, because everyone who is doing work in ML doesn't want to waste time making sure their C Cuda kernels compile. In the same way, nobody is going to care if they get the API headers right, or if their strings are correctly parsed when you can just invoke a dedicated LLM (which will likely be highly specialized small model able to run on local hardware) to do all that.
You can scream and cry as much as you want how that is bad, how its slow, but nobody is going to care because shit is going to get built faster. Ever notice how despite the massive layoffs across tech, there isn't service degradation in any sector? Good luck trying to sell your Rust skills in the future lol.
Someone responded to a previous comment of mine [0] positing a Peter principle [1] of slopcoding — it will always be easier to tack on a new feature than to understand a whole system and clean it up. The equilibrium will remain at the point of near, but not total, codebase incomprehensibility.
Yes. And as the models get better, it works better. But at one point you do have to understand the code because it's also just guessing as to what your actual intentions are.
It doesn't know what mess you want to clean up. A lot of times AI just starts making up new patterns on top of other patterns and having backwards compatibility between the two. How does it know which one you actually like?
A non-technical friend of mine has just won some hospital contracts after vibecoding w/ Claude an inventory management solution for them. They gave him access to IT dept servers and he called me extremely lost on how to deploy (cant connect Claude to them) and also frustrated because the app has some sort of interesting data/state issues.
What concerns me about this is that as these stories multiply and circulate people will just completely stop buying software/SAAS from startups, because 90% or more will be this same thing. It will completely kill the market.
Or you end up with a certification process, which will of course introduce it's own problems but startups doing things the right way and not just "moveing fast and breaking things" can thrive.
Those are custom software or heavily customized implementations of ERP and similar systems for very large organizations. I’m talking more about the SMB market where today it’s possible for a small team to carve out a niche and make a nice living or even bootstrap a venture that competes with a large player that has poor UX or antiquated feature designs.
The reason Oracle can continue failing at those massive projects is simple: everyone fails at them routinely and often it’s the customers fault.
I used to gripe about various ERP companies but after having dealt with enough, yeah, that's just what the world of ERP systems is like. You will spend your time even with the best of them desiring to scream endlessly at everyone who works there. And they also know your pain but are powerless to help.
>The reason Oracle can continue failing at those massive projects is simple: everyone fails at them routinely and often it’s the customers fault.
It's even simpler. Youre not paying oracle for some delapidated HR system. You're paying for the legion of accountability that is their on-site engineers to fix stuff for you when things screw up. You're essentially subscribing to a team of engineers you don't need to directly pay salary and benefits to.
People who think you can out efficiency that kind of accountability don't understand how large orgs think.
But the Torment Nexus is such an interesting technical challenge! and I don’t personally torment people: I just move protobufs around! - Software Engineer #1 and #2 excuses
> On January 3, 2022, the jury found Holmes guilty on four of the seven counts related to defrauding investors: three counts of wire fraud, and one of conspiracy to commit wire fraud. She was found not guilty on four counts related to defrauding patients
This hospital will learn some hard lessons. I hope their backup strategy is good. I'm surprised they can field software from an entity that isn't SOC2 & HIPAA certified.
No worries! At worst, the contractor can just tell Claude to make sure the hospital knows they're appropriately certified. And the hospital can use Claude to make sure the certs are valid. Everybody wins, except the ones who end up dead. Or with their health destroyed.
I was going to say to open yourself up as a contractor and scape some of the money off top. But it sounds like you dint need that opportunity.
That sadly does seem to be the trajectory of 5-10 years from now, though. I can't speak to if "AI is the future" of 30+ years from now, but these coming years sounds rife for "janitors" to clean up all the slop being produced by newly empowered idea guys
I work at a university and we still have some workstations that need IE as well, for a healthcare vendor app that needs ActiveX. Up until recently we even had some machines running Windows 7.
This is going to happen all over. Company I'm currently contracting with has gone AI everything (aka technical debt hell), and they're gonna suffer for it. I'm glad my consulting contract ends in 2 months. I don't want to be around for the crash
As a cybersecurity IR professional as much as I hate to see this happen to a hospital this kind of thing is responsible for essentially tripling my income over the last 3 years.
As a SWE that has only ever worked for an employer or on his own projects, this makes me wonder: how would someone even get such a contract? Did this person already have a consulting business? Do you just call up random hospitals and ask if you can demo an inventory management system for them? Did this person already know people at the hospital? I know technical folks that do independent consulting, but even with a vibecoded product, how is it that anyone can just get such a contract?
People really have a misconception about the sums of money that companies operate on on a regular basis. If you are a people person and know essentially how to sell yourself, you can "scrape" money on the fact that nobody is going to look or think too hard about some contract that represents a tiny fraction of the years budget.
That still leaves the question of how one gets their foot in the door. Lots of us are aware of the budgets but we don't get how's sales work at that level.
That's what it means to be a "people person" in the context of trying to sell a product, yes. Getting within 2 degrees of a decision maker can open up millions for you, while being a rounding error for every company you work with.
I'd really like to know how he won contracts, just in general. Did he have some connections. And he doesn't even know how to get it to run on a server by himself? There's millions of people that can do that, if he can win contracts why worry about vibe coding at all, just hire someone to do it. Winning contracts is the challenge in my view.
> Somewhere in the future, the new software engineering will be primarily about principles to avoid this in the first...
It's really nowhere near as complicated as making distributed systems reliable. It's really quite simple: read a fucking book.
Well, actually read a lot of books. And write a lot of software. And read a lot of software. And do your goddamn job, engineer. Be honest about what you know, what you know you don't know, and what you urgently need to find out next.
There is no magic. Hard work is hard. If you don't like it get the fuck out of this profession and find a different one to ruin.
We all need to get a hell of a lot more hostile and unwelcoming towards these lazy assholes.
This might not pan out to be the glorious victory of human craft as you’re imagining it to be.
Here’s a slightly different future - these AI rescue consultants are bots too, just trained for this purpose.
Plausible?
I have already experienced claude 4.7 handle pretty complex refactors without issues. Scale and correctness aren’t even 1% of the issue it was last year. You just have to get the high level design right, or explicitly ask it critique your design before building it.
This. I have this buddy, who is not an idiot by stretch of the imagination and more adventurous than me in some ways ( I don't really run agents on my machine ), but when I was looking at his prompts, I sometimes question how he gets anything done at all. It is vague and angry demands.
Not sure about the angry part, but vague sometimes works really good. The important part is to have enough good context pushed into the context window beforehand (codebase explorations, docs, etc). Then a vague prompt of the general direction gives the autocomplete more “freedom” to figure out the “best” approach given the context.
Doesn’t work well ofc in a one shot situation with no context.
> Maybe in the future but certainly no evidence of this anytime soon
Here's some anecdotal evidence from me - I cleaned up multiple GPT 4.x era vibecoded projects recently with the latest claude model and integrated one of those into a fairly large open source codebase.
This is something AI completely failed at last year.
Maybe you should try something like this or listen to success stories before claiming 'certainly no evidence' in future?
I'm no expert, but the skeptic's opinion I've heard would be to ask:
What evidence is there that we're not at or close to a plateau of what LLMs are capable of? How do you know the growth rate from 2023 to present will continue into 2029? eg. Is it more training data? More GPUs? What if we're kind of reaching the limits of those things already?
Since we're not experts, we treat it as a black box. What are the results? Is the quality of the results improving? Is the improvement accelerating or decelerating?
And the answer appears to be that the improvement is accelerating. So how could it be stopping?
I don’t think improvement is accelerating. We went from “computers can’t do these things at all” to “now they can” in a few years with the discovery of transformers, and now we get “it can do the same things, except incrementally better, at a drastically higher cost” every few months.
I don’t think that the current AI paradigm has infinite headroom for improvement, similar to how every other AI approach before it eventually hit a limit.
Incrementally, higher cost? A model I'm running on a 10 year old entry level computer is better at programming than GPT4. Those are multiple orders of magnitude of improvement in a few years.
And the link I posted shows the amount of work a query can do increasing non linearly. You can explore the site for more detail and a graph that shows error rates getting halved every couple of months.
No one said anything about infinite. It doesn't mean we don't have headroom to spare.
Software itself took 80-120 years to get where it is today depending on how you count. Time is on AIs side here.
Ultimately, you are describing a fundamental problem with induction -- Hume's problem of induction to be specific. How can we know that anything that has been shown empirically in the past will continue to be true - we can't. Best to investigate mechanistically:
I don't see why we would assume that we are at a plateau for RL. In many other settings, Go for instance, RL continues to scale until you reach compute limits. Some things are more easily RL'd than others, but ultimately this largely unlocks data. We are not yet compute/energy/physical world constrained. I think you would start observing clear changes in the world around you before that becomes a true bottleneck. Regardless, currently the vast majority of compute is used for inference not training so the compute overhang is large.
Assuming that we plateau at {insert current moment} seems wishful and I've already had this conversation any number of times on this exact forum at every level of capability [3.5, 4, o1, o3, 4.6/5.5, mythos] from Nov 2022 onwards.
I think we're close to the plateau of what LLMs can do, but they will keep improving. IMHO the results are already showing diminishing returns.
The (leading) LLMs work by consensus, like Wikipedia, Openstreetmap, web search engine or opensource movement.
What I mean is if I ask LLM "create a linked list", its understanding (of what I want) is already close to the expected ideal. Just like Wikipedia article on linked list, for example.
But the LLMs will continue to improve in breath and depth of understanding the world, although technically (what they CAN do) they probably already peaked. Similarly, OSS movement technically peaked in the 90s with the creation of compiler, operating system and a database; doesn't mean that new opensource isn't being created.
There is so much money at stake, and so much money pouring into AI development, that I think we are going to continue to see gains for a while. People keep coming up with new agent harness techniques like chain of thought, tool calling, and memories. And then the big LLM companies figure out how to actually train their models to optimize the use of those techniques. To claim that we are reaching the top of the plateau is to claim that we are out of effective ideas for improvement. I think that's a ridiculous claim, the technology is too new. And because of the strong incentives to keep making these things better, it's pretty much a given that people will continue to explore ideas until we really are out of effective ideas. I don't think anyone apart from professional AI researchers have any idea where this is all going to settle.
Well depends what you mean by peak. I was answering parent's question of what LLM's CAN do. It's not about peak of technology or humanity itself.
LLMs (or specifically GPT algorithm) are 8 years old. It has matured as a technology. I am not sure how you imagine it being significantly improved, from a user point of view, without some kind of paradigm shift (i.e. something significantly different from GPT or LLM).
Although I can imagine one important social innovation yet to come - a generally available big public LLM, that "anybody can train". We had a technology of "encyclopedia" for years (famously Brittanica); yet the concept of Wikipedia has been a truly new take on encyclopedia.
Also, new kinds of AI might emerge - for example we might formalize all types of human reasoning and build a reasoning AI, as well a model of human language, from scratch rather by training via GPT (and thus, more understandable and potentially smaller). But that won't be an LLM.
> I am not sure how you imagine it being significantly improved, from a user point of view, without some kind of paradigm shift
I proposed how. New harness techniques and new training data/techniques, so the harness gets better and the LLM can be trained to work better with the harness. There's no reason to believe we're out of momentum for improvement in that direction.
Yeah but what do you mean by (substantially) better in this context, what is the outcome? Modern models can understand the requirements as well as humans can.
However, they also make mistakes like humans, I don't think a better harness or better training will fix that, because fundamentally, they cannot read your mind, if you put in an ambiguous prompt.
I like to compare the process of turning inexact text to formal language to an error-correcting code. If you haven't made too much mistakes or have been precise in the specification, it will self-correct and do what you want. But if your input is too ambiguous, it will never do exactly what you want, but something close to it. And people (who are using AI) are still learning where is the boundary and how to tell.
The companies building these models are training them to react to typical expectations. If you have some special need, you will always have to tell the model, otherwise it will not know your exact context. And the harnesses have many tools for that or try to do that automatically already.
I have personally had success telling Claude that some AI-written system is too complicated and ask it to rewrite it in a more logical way. This sometimes results in thousands of lines of code being deleted. I give an instruction like that if I see certain red flags, eg:
1) same business logic implemented in two different places, with extra code to sync between them
2) fixing apparently simple bugs results in lots of new code being written
It’s a sign I need to at least temporarily dedicate more effort to overseeing work in that area.
I somewhat agree with the AI psychosis framing of the OP. It takes some taste and discipline to avoid letting things dissolve into complete slop.
AI is currently, actively getting better. That might stop in a year, and you can argue whether it’s linear or exponential, but it’s very difficult to argue that it won’t get better in the near term. On the other hand, arguing that we hit a plateau at this time is just ignoring reality.
There are untold billions of dollars to be had if you can make this future come to pass. You don't need AGI to make it happen either. You just need to keep making the context windows bigger and keep coming up with updated training data. It's not the outcome I want, but it really does feel within reach. The only limiting factor is going to be token count and cost to process/generate those tokens. But if you don't particularly care about quality, costs are going to have to go up by several orders of magnitude before you start to regret firing your software engineers.
I don't know what happens in a decade when there are no junior engineers, skilled senior engineers are becoming rare, and the only data left the train LLMs on is 200th-generation slop. But AI slop being qualitatively slop is not enough of a obstacle to prevent that future from coming to pass. And billions of dollars will be "saved" along the way.
Companies are already putting billions out there just to secure and produce training data. And that's the isseue; spending X billions to make X-Y) billions isn't a profit, it's a gamble hoping Y becomes negative (or at least close to zero with a commodity that is profitable) . Real profits have not been made directly from the work on AI as of now. It's made from marketing a narrative of AI working.
That's what makes this whole house of cards dangerous. The prescription to psychosis is profitable. Aka, selling a grift.
With GPT 5.4 or 5.5 I did not notice degradation in performance when it was working on a large 5k line file containing a WebView, JS scripts, as well as native UI.
I instructed it to split it up anyway, yet I wonder how often the concerns around the mess are imaginative rather than practical.
> I think AI rescue consulting is going to be come a significant mode of high value consulting
I thought the same when I saw development outsourced to Indians that struggled to write a for loop.
I was wrong.
It turns out that customers will keep doubling down on mistakes until they’re out of funds, and then they’ll hire the cheapest consultants they can find to fix the mess with whatever spare change they can find under the couch cushions.
Source: being called in with a one week time budget to fix a mess built up over years and millions of dollars.
The complexity you would come to the rescue to solve, would that be from AI or from the style of programming you let the AI have? I mean, you have very different problems if you use functional style vs object-oriented. It is up to the programmer to realize they want a functional style and request that from the AI, as much as possible. Even AI cannot imagine every state transition, unless it is so smart that it should be the one telling you what to do.
Heh. Got a customer recently around this. Entire infrastructure and CI/CD vibecoded. They half implemented Kubernetes in Github Actions that were several thousand lines long and impossible to understand.
I think the problem will get worst. I dislike the marketing around AI, but I do think it is a useful tool to help those who have experience move faster. If you are not an expert, AI seems to create a complex solution to whatever it is you were trying to do.
> If you are not an expert, AI seems to create a complex solution to whatever it is you were trying to do.
I've been watching non-developers vibe code stuff, and the general failure mode seems to be ignorance of 3-pick-2 tradeoffs.
They'll spam "make it more reliable" or some such, and AI will best-effort add more intermediary redis caches or similar patterns.
But because the vibe coders don't actually know what a redis cache is or how it works, they'll never make the architectural trade-offs to truly fix things.
I’ve noticed something similar with vibecoded game rendering logic submitted by peers. Sometimes it will be peppered with extraneous checks for nullptr, or early returns on textures that have zero size.
I often wonder if it’s the statistical nature of the LLM mixed with a request in the prompt.
AI LOVES defensive coding. I asked you for code to filter and reduce an array. I didn't ask you for a method that makes sure the array exists and is an array before it does anything else.
I'm with you on this one, having "vibe coded" some smaller internal tools on GPT 5, and then re-vibed it on Opus 4.6 and 5.5 -- they basically just fixed all of the problems without me doing much of anything other than prompting it to look at the existing code and make it "better".
Pretty much. We're intensely vibe coding something that has gone through so many requirement changes. The code has become very gnarly. I took a stab at basically one prompt rewrite of the whole thing. And it wasn't there, but it was 80% of the way there. and a hell of a lot cleaner.
Are you sure about this? Yes, there is a stable set, but they are used in all of the wrong places, particularly in places where they don't belong because juniors and now AIs can recite them and want to use them everywhere. That's not even discussing whether the stable set itself is correct or not - it's dubious at this point.
Those design principles it will take us 20 years to learn are just the principles for writing good maintainable, debug-able, understandable code today. Will just take 20 years to figure out they still apply when AI writes the code, too.
Many teams did this before AI too. They start faster and end up with hard to refactor or extend code. For example, think of teams that don’t version their API /api/v1, that blocks a whole category of refactoring and extensions. Or teams that have random state transformation routes instead of following restful actions.
Interesting perspective. Fundamentally at conflict with the data, science, and 20+ year trends of AI coding systems - to the point of dogmatism. But interesting from a sociological point of view.
is this true because training companies have not been training AI for both performance and brevity (or some other metric like that)? If this becomes a much more serious issue surely they would adjust the training processes
What you're describing really isn't a new problem for organizations. Historically it's been a team of humans not using AI who gets over their skis and they have to have other more capable humans (also not using AI) to bail them out.
I don't understand this point of view at all. There's a symmetry that is going entirely unappreciated by most of the comments in the thread: just as I can give Claude X,000 words of text to use to describe the code I want it to write, I can also give it some existing code and ask for X,000 words of text explaining what it does. (Call it, oh, I don't know, a "spec," maybe.)
The explanation, in turn, can be fed back to recreate the functionality of the original code.
At that point, why care about the code at all? If it works, it works. If it doesn't, tell the model to fix it. You did ask for tests, right?
That is where we're indisputably headed. It's not quite a lossless loop yet, but those who say it won't or can't happen bear a heavy burden of proof.
Code is not spec. There is an implementation spectrum.
On one end, you have code that can perform only the behaviour explicitly declared in the spec, but has to be thrown away and rewritten for any new or updated spec.
On the other end, you have code that implements or anticipates a wide range of future possible specs including the given one.
The AI can operate on any point on this spectrum, but it's not very good at choosing. The more complex the software, the more such choices need to be made.
When the number of bad choices reaches a certain critical mass, even a skilled engineer becomes powerless to undo all the bad choices, and even a powerful model becomes unable to reduce it back to a coherent spec.
Some people are mindful about what they get and don't get from amazon and don't die from prosperity. ("you might use AI to increase your prosperity")
the rest of the world eats too much and dies of heart disease/diabetes. ("the rest of the world will flounder more and AI will do more stuff to them than for them")
I've already done a handful of these gigs for early vibecoded products that had collapsed in on themselves. The scope of work was to stabilize the product and only make existing features work.
The issues have all been structural, not local. It's easier to treat it like a rewrite using the original as a super detailed product spec. Working on the existing codebase works, but you have to aggressively modularize everything anyway to untangle it rather than attack it from the top down.
All of these projects have gone well, but I haven't run into a case where a feature they thought was implemented isn't possible. That will happen eventually.
It's honestly good, quick work as a contractor. But I do hope they invest in building expertise from that point rather than treating it like a stable base to continue vibecoding on.
I've worked with many people over the years. A bunch of product people have struck out to make their own thing now that they can get a feedback loop going. I just keep in touch with people. They know my services are available, so if they have a need they reach out.
The greatest asset in this type of work is genuinely liking people, being good at what you do, and keeping in touch. My email is easily findable for a reason.
So, there is no secret sauce? Just work for people and have a hand at their contact info?
The one part I do wonder is how to "keep in touch". Maybe it's a generational thing as a young millennial (some would call it "Zillenial") but the biggest issue in my networking over the year (cough and the dating scene cough) is ghosting. You think you hit it off, try to follow up the day after, and proceed to never again hear from them.
> Purely AI written systems will scale to a point of complexity that no human can ever understand
But won’t those more complex systems presumably solve more complex problems than the systems that humans could build? Or within a comparable time?
I think it is reasonably safe to assume at this point in the game that these AI systems are increasingly able to reason rigorously about novel problems presented to them, of ever increasing complexity and sophistication.
That sounds so horrible, though. It's akin to people working as COBOL devs because someone has to do it, so they'll get the big bucks. Except I've never heard of anyone who actually likes COBOL and the more I've learned about how mainframe development actually works, the more horrified I've become haha. Dealing with an LLM spaghetti codebase sounds like hell.
My company and my buddy's company, we're experiencing the same thing. We are trying to fire a SAAS vendor and it's become the hot new project. Now we to these meetings with 50 different people that are allegedly stakeholders, two or three product managers who have already vibcoded their version of something.
Ultimately, if you want to move fast, it's better just to have one engineer vibe coding something. but, that engineer is under so much pressure. Now he's got a legacy mode and another legacy mode because the requirements keep changing. And now there's a deadline in four weeks.
This all could work just fine, but the ungodly amount of attention that this world is getting puts too many cooks in the kitchen, which is always a recipe for disaster.
I shut down AI Agent fanatics on the regular. But chop one head off there and two take its place. And I say that as someone working with Claude and Codex daily. While they are both incredibly good at clearly described and defined atomic tasks, application scope makes them lose their minds and the slop ensues.
The race to invent variants of Gas Towns, Ralph loops, pump out videos, blogs, etc. showing off greenfield development with cleverly named agents running in parallel is another case of engineering people diving head first into Resume Driven Development.
Sure there are industry changing things going on. What if you're working on an app thats a decade old and has had different teams of people, styles, frameworks (thanks to the JS-framework-a-week Resume Driven Development)? Some markdown docs and a loop of agents isn't going to help when humans have trouble understanding what the app does.
I work for a small telecom services provider whose current VP immediately set an AI course when stepping on board 6 months ago. Involving AI in everything and every task is now our first priority - across all employee segments, not just us system developers - and leadership is embarking on a program to measure employees' AI usage levels as a means to gauge everyone's individual efficiency. It's like the era of the evangelic crypto bros all over again.
There's a lot of people writing bad code. With AI being forced top down (with the promise of turning people into 10x-ers), we're going to get a lot of people writing bad code 10x faster.
I really do worry - I especially worry about security. You thought supply chain security management was an impossible task with NPM? Let me introduce to AI - you can look forward to the days of AI poisoning where AIs will infiltrate, exfiltrate, or just destroy and there's no way of stopping it because you cannot examine the internals of the system.
AI has turbo charged people's lax attitude to security.
Not security, but I ran into a related supply-chain issue recently. I needed a library to perform a moderately complex task, and found one in the ecosystem I was working with that had been around for a while, appeared reputable, and passed my cursory inspection. So I dropped it in, got the feature implemented, and moved on.
Some time down the line, I discover CPU being maxed out, which is showing up in degraded performance in other parts of the system. I investigate, and I trace the issue to a boneheaded busy loop in this library that no human with the domain expertise to implement the library would have written. Turns out I'd missed one deeply-buried mention in the README that maintenance was being done via AI now, and basically the whole library had been rewritten from the ground up from the reliable tool it used to be to a vibecoded imitation.
Yeah, yeah, sure, bad libraries existed before all this. But there used to be signals you picked up on to filter the gold from the dreck. Those signals don't work anymore.
I don't think it's helpful to call this psychosis. N
Beyond that I don't think it's even irrational.
It is definitely factual that there is a complete paradigm shift in the prioritization of quality in software. It's beyond just AI side effects, and now its own stand alone thing.
There have always been many industries, companies, and products who are low on quality scale but so cheap that it makes good business sense, both for the producer and the consumer.
Definitely many companies are explicitly chosing this business strategy. Definitely also many companies that don't actually realize they are implicitly doing this.
Wether the market will accept the new software quality paradigm or not remains an open question.
The hype or psychosis is mainly by mediocre/non expert/middle manager/you name it, especially when a person who never wrote a single line of code suddenly is making a wall of text, and it actually works!? Oh my!!
But in reality, anyone who knows their field and are going after certain specific issue, they will find soon how AI is nothing but an assistant, sure it can help and automate some stuff, but that’s it, you need to keep it leashed and laser focused on that specific issue. I personally tried all high end ones, and I found a common theme, they are designed to find a solution or an answer no matter what, even if that solution is a workaround built on top of workarounds, it’s like welding all sort of connections between A and B resulting in a fractal structure rather than just finding a straight path, if you keep it going and flowing on its own, the results are convoluted and way over complicated, and not the good complexity, the bad kind.
The entire problem is vibe coding is only good for demos, prototyping and finding signs of product market fit without actually releasing a product into the market.
You should not release a product into the market unless you have a good enough product that can keep you and your client compliant, safe and secure - including not leaking their customer info all over the place.
Prompt injection risk, etc. are massive for agentic AI without deterministic guardrails that actually work in practice.
Stop testing in production if you're shipping in a regulated industry. Ridic!
If you're not technical, you can get someone who is after signs of p-m fit, demos, but BEFORE deployment. This is common sense and best practices but startup bros dgaf because they're just good at sales and marketing & short term greedy.
I saw this first hand at a company, and I think this is what happens when you combine FOMO with an utter lack of industry best practices. No one knows where they are going, but are convinced they are not getting there fast enough.
What's more, the only people they talk to about it are others at the same company. There is no external touchstone. There are power dynamics from hierarchy. No new ideas other than what is generated within the company. In other circumstances, this is a textbook environment for radicalization.
I would encourage all leadership to take a deep breath. You have time to think slow.
Totally unrelated pet peeve of mine, I hate when people write this: "MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery)".
You first use the full words and then introduce the acronym that you're going to use in the rest of the text: "Mean Time Between Failures (MTBF) vs. Mean Time to Recovery (MTTR)".
With the latter, readers understand the term immediately, even if they don’t know the acronym. And they don't have to read these weird letters before getting the explanation.
Amazing how the dev community is suffering from a similar inability to approach the subject of real world AI efficiencies and business benefits. I don’t think it’s helpful to accuse the other side of psychosis. It disqualifies any data or experience they bring to the conversation.
It seems the diagnosis of psychosis is too quick: it seeks to reestablish the frame of expert for the developer identity that is being replaced by it.
“It feels like entire companies are deluded into thinking they don’t need me, but they still need me. Help!”
The broad sentiment across statements of this “AI psychosis” type is clear, but I think the baseline reality is simpler. How can you be so certain it’s psychosis if you don’t know what will unfold? Might reaching for the premature certainty of making others wrong, satisfying that it might be to the ego, be simply a way to compensate the challenges of a changing work environment, and a substitute for actually considering the practical ways you could adapt to that? Might it not be more helpful and profitable to consider “how can I build windmills, ride this wave, and adapt to the changing market under this revolution” than soothing myself with the delusion that all these companies think they don’t need me now, but they’ll be sorry.
The developer role is changing, but it doesn’t have to be an existential crisis. Even though it may feel that way — but probably it’s gonna feel more that way the more you remain stuck in old patterns and over-certainty about how things are doesn’t help, (tho it may feel good). This is the time to be observant and curious and get ready to update your perspective.
You may hide from this broad take (that AI psychosis statements are cope) by retreating into specific nuance: “I didn’t mean it that way, you’re wrong. This is still valid.” But the vocabulary betrays motive. Resorting to clinical derogatory language like “AI psychosis” invokes a “superior expert judgment” frame immediately, and in zeitgeist context this is a big tell. It signifies a need to be right, anda deeply defensive pose rather than a clear assay of what’s real in a rapidly changing world. The anxiety driving the language speaks far louder than any technical pedantry used to justify it, and is the most important and IMO profitable thing to address.
I feel in a really weird position where I both really dislike what AI is doing to the experience and practice of writing code, to the point where I want a job doing literally anything else besides using the computer, but also think that these tools are extremely powerful and only getting better.
I think Mitchell's point is well taken -- it's possible for these tools to introduce rotten foundations that will only be found out later when the whole structure collapsed. I don't want to be in the position of being on the hook when that happens and not having the deep understanding of the code base that I used to.
But humans have introduced subtle yet catastrophic bugs into code forever too... A lot of this feels like an open empirical question. Will we see many systems collapse in horrifying ways that they uniquely didn't before? Maybe some, but will we also not learn that we need to shift more to specification and validation? Idk, it just seems to me like this style of building systems is inevitable even as there may be some bumps along the way.
I feel like many in the anti camp have their own kind of reactionary psychosis. I want nothing to do with AI but I also can't deny my experience of using these tools. I wish there were more venues for this kind of realist but negative discussion of AI. Mitchell is a great dev for this reason.
I've never had more fun coding, but the key is actually still writing the code yourself. The LLM has terrible judgment but an encyclopedic knowledge and the ability to pick out important details in a sea of information. Their worse use is producing code, but somehow that gets all the energy. Being an LLM babysitter is energy draining and you feel less and less in control. No job is worth being miserable doing something that you used to enjoy.
I've used both ChatGPT and Claude, they seem interchangeable for my needs. I only use the web prompt interface except for the rare occasion that it is helpful for it to have the context of my entire project. I think less is more when it comes to LLM interaction, but sometimes they are exactly the right tool for the job.
I didn't realize you wanted that information too, I could probably bore someone to death talking about it.
Planning: I often ask it to help me plan an approach if we are dealing with something I don't have a lot of experience with, most recently working with the DOM. If there is a library or an API that is new to me, I ask for an overview and run my plan by it for comments. Feed it the documentation and it is like talking to author.
Coding: I have a pretty reliable sense for when a section of code that I want to write is obvious enough for the LLM to one-shot based on the other code in the file, and on those occasions I call in completion. I do this with code that I can verify at a glance.
Analysis: If I have any uncertainty at all about the code I've written, I run it by the LLM to find issues. Out of all the other uses, I think this is the most productive and time saving. If I run into a bug and I'm stumped, I show it the section of code. I'm amazed at how good it is at finding mistakes.
I'm working solo as a full stack developer coming from a different background, so I sometimes find myself out of my depth. Having access to the breadth of knowledge that an LLM brings and its attention to detail has been game changing. I've tried a couple agents and configuring them to work competently seems like a rabbit hole, and I like the tight control over the context that chatting with the web prompt interface brings. It seems like half the value is putting into words my intent, it forces me to have a cohesive understanding myself. It is like rubber duck debugging where the duck can actually talk back and sometimes provide the critical part that I'm missing. I have it speak like a pirate which is just for fun but sometimes the sailing metaphors that it uses are really intuitive.
I've been working on a C++ backend for F# and while I'm very familiar with F# and it's AST I barely know C++. The amount of time I save being able to ask things, check my understanding, get design patterns, and paste issues I'm having for a fix is insane
I ran into an issue where I was getting a segfault and everything looked right in the debuggr, including expected values near the segfault. Turns out I wasn't using placement new somewhere I needed, and the data for the object was getting copied but not the vtables. I have no idea how long it would have taken me to figure that out on my own because the segfault was coming from so far away
I haven't had the opportunity to use LLMs much for coding since I'm not working right now, but I can second how much of a boost just getting specific answers to my questions instead of reading tons of whatever online searches return is.
Rubber duck that talks back is a nice way to put it
working in a large codebase I use Claude for code understanding and the code reviews from Macroscope have caught bugs for me a bunch of times. Usually if I use claude it’s for refactoring a and source to source transformations that would be too confusing for me to figure out how to do with e.g. ast-grep, but that I can prompt in a minute or two and then have claude work through it. It’s stuff I could do without LLMs but it’s less effort to use them. I don’t let it write new code, because it decays the process of programming as theory building.
not the person you're replying to, but someone who agrees with the gist of their message - I personally use Claude Code as a better Google search for debugging and syntax.
It used to be "oh, why am I getting an error on line 352, let me google the error message and wade through Stack Overflow answers" now it's "Claude, why am I getting an error on line 352? Ah, it's because $REASON, let's see if that fixes it, yes, thank you."
Obviously reading the official documentation is very useful, but sometimes you can't find anything that relevant to your exact use case, and forums are also very useful, but it can take hours or even days to get a reply to question when the LLM can do it in like a minute.
In my experience, its the opposite. The AI is very good at writing code, but it is unreliable at any kind of design. I use it as a fancy form of autocomplete. I give the broad strokes: "add a method here and change all but this one caller to use the new method", "Apply this design pattern here for this change but don't do this other thing". It completes the task reasonably well and sometimes even remembers to run the code formatter and check that tests pass.
If I ask it to me produce a design, I'll almost always end up with something unworkable or inefficient.
Though if you push it hard enough then it can sometimes give you a good description of what existing code does and how it does it (which can be easily verified).
Can you pro-AI people at least agree on what is it even useful for?
Every thread is endless back-and-forth between the "AI works great and vibe coding is the future" and "no, AI works great as long as you don't vibe code" camps.
My biggest complaint about AI is getting it to lock onto current or specific information has been darn near impossible. Its definitely there in its training data but for the life of me I cannot get it to stop bleeding long outdated or external information into its responses.
> But humans have introduced subtle yet catastrophic bugs into code forever
So now the AIs will do more of that, at superhuman speed.
> will we also not learn that we need to shift more to specification and validation
We'll just quickly learn what we've been trying to do for decades, while also treading water in floods of more code than has ever been written before? And some of the motivations to write correct code are being deflated - "just vibecode it again and see if the bugs disappear, it only took a week and $200."
I think the commenter was referring to formal verification with "specification and validation": have the LLM emit formal proofs about invariants etc.
Currently the bugs are found by people using LLM's but aren't the developers. As more projects start getting access to compute, they can run those LLM searches for bugs themselves, and can simply prevent shipping the bugs.
I'm surprised no one has tried making any statistical analysis of bug densities, and "bug authors" in an attempt to identify untrustworthy developers, regardless of intent. Given a dataset of authors and prior bugs, it may help find more bugs by tracking their pull requests with higher scrutiny...
Some people may end up with an eternal stain if they've been taking money to submit vulnerable code to code bases...
> I feel like many in the anti camp have their own kind of reactionary psychosis.
You're using psychosis wrong. My literal reality is my entire industry trying to use Ai as an excuse to payoff hundreds of thousands, to millions of American engineers in lieu of outsourcing work overseas. It's having hostile promots to use AI that never truly go away (if you're even given an option to turn off the prompt). It's seeing an emerging generation completely stunted because AI's best use is to cheat the education system and ruin the youth's critical thinking. It's looking in apallment at proposals for data centers that take more energy than the state actually has.
And while you can try to call these exaggerations, you're falling into the very psychosis of this article if you want to deny this reality as a whole. "but the tech is making us so productive" is not a valid justification to literally collapse human society as we know it.
Maybe this is what will turn software engineering into an Engineering field.
Right know, prompters are setting up whole company infrastructure. I personally know one. He migrated the companies database to a newer Postgres version. He was successful in the end, but I was gnawing my teeth when he described every step of the process.
It sounded like "And then, I poured gasoline on the servers while smoking a cigarette. But don't worry, I found a fire extinguisher in the basement. The gauge says it's empty, but I can still hear some liquid when I shake it..."
If he leaves the company, they will need an even more confident prompter to maintain their DB infrastructure.
> Maybe this is what will turn software engineering into an Engineering field.
Oh man, I think you may have touched the third rail here.
My first job out of high school was as an AutoCAD/network admin at a large Civil & Structural firm. I later got further into tech, but after my initial experience with real Engineering, "software engineering" always made my eyes roll. Without real enforced standards, without consequences, it's been vibe engineering the whole time.
In Civil, Structural, and many other fields, Engineers have a path to Professional Engineer. That PE stamp means that you suffer actual legal consequences if you are found guilty of gross negligence in your field. This is why Engineering firms are a collective of actual Professional Engineer partners, and not your average corporate structure.
The issue is that in software dev, we move fast, SOC2 is screenshot theater, and actual Engineering would slow things way down. But, now that coding is fast, maybe you are correct! Maybe vibe coding is the forcing function for actual Software Engineering!
___
edit: I just searched to see if my comment was correct, and it turns out that Software PE was attempted! It was discontinued due to low participation.
> NCEES will discontinue the Principles and Practice of Engineering (PE) Software Engineering exam after the April 2019 exam administration. Since the original offering in 2013, the exam has been administered five times, with a total population of 81 candidates.
Note that other types of engineering are also often vibes based. The mechanical engineering for a rocket engine is extremely rigorous but the engineering for an injection molded housing for a cheap cell phone is a lot more about following a few heuristics and getting it out the door. Even in robotics where I work, it’s mostly about making parts that pass whatever acceptance tests you come up with. In civil engineering and aerospace failure costs human lives and millions or billions of dollars. In robotics maybe you have some machines fail in the field but in many instances you have one overarching safety system and many of the parts are irrelevant to that. The camera housing for example. So no paper trail or mathematical design validation is required to prove you designed it right. Often those are desirable but if you just manufacture it and test it a lot you’re probably fine.
This was something I noticed in my early career in mechanical engineering and later doing PCB design and software for robotics. It’s easy to find firms that just need adequate parts without the professional certifications or ass-covering calculations of other engineering fields.
All this to say, it’s not just software versus the rest of them. From my position, civil and aerospace seemed more like the exception while much of the rest of the engineering world is more vibes based.
What makes it a profession is not just the certification, it's the burden of responsibility for consequences. Your lawyer, accountant, and real engineers carry "we need insurance for this" level of risk in their work, all the way up to "can go to prison for getting things really wrong".
Until and unless software is held to that standard, software will never be engineering and always just a craft that can be performed to any or no standard.
Eh writing software for healthcare, or aircraft or self driving cars is more rigorous than an EE working on industrial lighting or toys.
Im sure for the most part, engineers in physical space deal with the same kind of tradeoffs software engineers make, where you try your best based on industry standards, personal past experiences without some way to prove what youve done is right
> Eh writing software for healthcare, or aircraft or self driving cars is more rigorous than an EE working on industrial lighting or toys.
That’s a relatively small field within the software industry.
Most of the work being done (adding new fields to CRUD apps etc) is glorified clerical work, where the people doing it are rightfully fearful of being automated out of existence by AI.
Now imagine if you’re one step removed. You don’t see the cigarettes, smell the gasoline, nor see the fire extinguisher gauge. You only see the servers running business-as-usual. Those “engineering” guys are always drama queens, you think. We have processes and fire extinguishers when shit hits the fan, right?
That’s basically every M2, and many if not most M1s, in the last 10 years. So fuck it. Why does any of it matters?
As a junior dev there is this pressure to produce code, add features, and investigate bugs within unprecedented time period. I know whole code base is fking up but i will still add that feature or do a sloppy bug fix without digging deeper.
In my experience, AI really lowered the bar for bad code in the name of delivering faster.
I have seen people write highly complex code where all the complexity was not necessary. Think: deep unnecessary branching, pointless error handling and retries which make no sense in our context, hand-coded parsing using regexps, haphazard data flow, functions which seem purely computational but slyly make API calls, pointlessly nullable model fields, verbose doc comments which describe the implementation instead of the contract. I could go on.
The worst part is, even when "prompted" by bad coders, it works in the end. Even has tests (ostensibly mock-ridden, a pet peeve of mine which always falls on deaf ears). So I cannot reject the PR without being an asshole.
I am no luddite. I make heavy use of AI, with all the skills / AGENTS.md / style guides and clear specs, then review every line of code, prefer testing with minimal mocking. I'd even say with right prompting, it can write better low level code than me (eg: anticipating common error conditions).
But my biggest fear about AI is how it enables normies with little to no understanding of CS principles to produce code faster which looks correct but slowly poisons the codebase.
I have a friend, smart guy, who is writing web services and “connecting them together” for a large firm; he has absolutely no programming experience.
Talking to him, he told me he couldn’t even reverse a string. He is at once many times more valuable than ever before to his company, but also far more dangerous than ever before.
This is what fascinates me. I have a friend, also a smart guy, who has made it to the point he’s at by being a kind of solutions expert. He’s an IT guy, basically. He’s very technical but has never claimed to be a software engineer. He’s writing software with Claude now. The other day he sent me a screenshot of some other team at his work asking him to shut off something he made that was brutalizing an API of theirs. I asked him if he had ever heard of a 429 or exponential back offs. He said no. How do you meta-prompt for that without knowledge?
You can create an agent in Claude with the role of Technical Lead / Architect and have it review your code. That depends on your agent specification. Just have ChatGPT generate that first.
If you get the logs you can feed them in and ask for improvements, that sometimes helps.
When I read the discussions about AI making code worse I keep bringing the same argument: people made bad code even before AI. Average coder is barely functioning and that's a fact.
And we were safe from them because they couldn’t produce a mountain of code every day. But soon many places will be buried under a planet of unmaintainable code. It’s adding friction and operational cost and often not adding value.
People could, however, learn to not make bad code. LLMs are incapable of that feat because they do not have any understanding or ability to reason. They are strictly worse than a human.
As others have elaborated, the problem is empowering them to ship mountains of bad code;
And yeah, many semi-technical M2s or even M1s can't distinguish bad code from good code, or worse bad architecture from good; this is golden time for those who are willing to sacrifice the future for present. Just burnnn'em tokenzzz.
> In my experience, AI really lowered the bar for bad code in the name of delivering faster.
I would've believed that 6 months ago, but not now.
If you have a good codebase with proper rails, hygiene and architecture, AI will produce better code than most engineers out there.
People forget that 90% of the field has always been charlatans barely able to implement a fizz buzz or go much beyond trial and error googling.
I'll say even more. I'm in the 10%, and it's increasingly clear to me that AI writes in minutes code that's better than mine.
Even stellar and respected OSS engineers are nowadays leveraging AI and guiding it less and less everyday beyond giving indications of what kind of data structure they may want for a complex problem or the kind of architecture they are looking for.
In any case, I don't like this field anymore, I have no joy from it, way too much work, way too many changes a human can cope with both on product and technological level (not even counting AI and its tooling itself). The interesting parts of thinking an entire afternoon or week experimenting to get that design right disassembling the pros and cons are gone.
Even if you want to do that, it's just faster to launch 6/7 worktrees with the different ideas and judge the results. But you don't get as intimate with the problem and the amount of information is way more than you can process.
Forgive my ignorance, but if the corpus of coding data was always 90% bad, isn't that the same data being used for training LLMs? How are they magically any better than that average?
I'm hand rolling a project right now because even frontier models I use bloat things beyond comprehension. Because I'm intimately familiar with the domain, I know the shape of things, how the data should flow, and so on, and if l even if I spec it clearly AI will write 2x to 5x the amount of code necessary to make something work.
"beyond comprehension" is a good way of putting it. I've been genuinely baffled by some of these AI designs - why any intelligent thing would write >10 lines of bloat for what should be a one-liner.
Proper rails, hygiene and architecture need to be actively maintained, they don’t just continue to exist in a developing codebase. Historically, a small proportion (the 10% as you say) had a disproportionate amount of influence on coding standards. When they can no longer keep up with that ongoing maintenance, which we’re seeing with the increased pressure to ship code, the hygiene will regress. We’re riding the tail of all the engineering practices we’ve developed as an industry.
This is what I’m seeing, anyways. Junior engineers are being rewarded for shipping so much code, it’s impossible to evaluate it all, and subtle changes in existing patterns are slipping through. Eventually all those subtle changes transform the rails.
So many fallbacks. So many function_exists. So much pointless type casting. I swear it’s like the system prompt is designed to waste as many tokens as possible.
> Maybe this is what will turn software engineering into an Engineering field
I think it’ll be the opposite. Maybe it’ll be what will eventually cement the field as “talent” based field. Just like it was difficult to quantify what makes a flute player better than another, how good your are at endlessly prompting a blackbox machine would be the only measure. The engineers of ol’ whoe developed kernels and drivers would be thought of as the “crazy people who put the flute against their temple to tune it” LOL. we don’t need people like that. You can just buy a flute tuning device. who gives a fuck? Can you make the next “Shake it, Shake it”?
I work at software in a medical setting. We are piloting an integration with a startup for measuring [some bodily variable relevant in ICU setting]. They are obviously vibecoding (docs are telling) and their API is failing in unexpected ways that they are not able to resolve. I am just waiting when this are going to harm somebody.
This is the pattern you will see when medium-successful ignorant people take o ver a system that was based on some kind of standard.
You can see the same approach is taken by Trump and other people.
“You have TDS!! He is actually doing good. He doesn’t follow rules because the system is rigged etc.”
These arguments border on religion because it is predicated on you believing their ignorant point of view in the first place.
Engineering and science is built on rigor and empirical evidence, it is not built by scammers/businessman/ignorant-people/politicians because that is just not how it works
This reminds me of Rich Hickey’s “Simple Made Easy” and his approach in making Clojure.
Even before LLMs generating entire programs, complex frameworks allowed developers to write the initial versions of programs very quickly, but at the cost of being hard to understand and thus hard to debug or modify.
Some of us are betting that the AIs will always be smart enough to debug, maintain and modify the programs written by AI, no matter how convoluted or complex. I’m not so sure.
That people don't realize full test coverage just means every line is hit, not that everything is correct is always funny to me. (I don't view as an argument against tests, but with AI it's especially important as if you're aren't careful it'll be very happy to make coverage that is not quite right.)
Just talked to an exec yesterday about their multinational company, where the newly-installed CEO just came in with "everyone needs to be using AI" and "we should be doing everything with AI".
I cautioned them that this a terrible idea -- you have business people who don't know what they're talking about, and all they know if "if we don't 'do AI' we'll be left behind because our competitors are 'doing AI'" (whatever tf "doing AI" means).
Yes, LLMs are a great tool. But they're not like some magic bullet you stick into everything. Use it where it makes sense, and treat it like you would other tools.
You make "doing AI" some kind of KPI in your org, and you're going to have people "doing AI" amazingly (LOC counts! tokens burned! tickets cleared!) while not actually being more productive, and potentially building something that is going to come down on your head for the next team to "clean up the AI mess".
I'd like to chime in and mention that its really obvious how to RL a coding agent to get the human addicted asap. and its also clear that there's a ton of $$$ to be made by doing this. therefore its done. the only LLMs I use are the ones I run locally because i know they aren't RL'ed for that metric (no incentive for the company that made them to make their open weights models addictive)
I think there's a few things, but its a little subjective and its more about the style the ai uses when doing these than the actual specific behavior:
- Nuggesting improvements to the code after finishing the task you gave it, very irritating when the improvements were obvious and the ai didn't implement them on its own
- Not trying very hard when implementing something, leading to bugs, which leads to more tokens used (this behavior can be incentivized and learned with RL)
Since its a known fact if a user continues a session after the LLM says something, its not hard to train against this. The least efficient way to do this would be to GPRO directly against the user base and try to get as many people talking to the AI, and with OAI having a billion monthly active users the least efficient method would work really well for them.
Hard to have sober talk about this since a lot of discourse is AI psychosis vs. AI naysayers. Does software quality seem to have taken a jump in the past few years to anyone? Not to me, seems to be getting worse. Think that's a decent signal. Can tell you I'm dealing with a non-technical VP who loves blast submitting vibe-coded PRs and while there's some quick wins, overall quality is bad, and we had our first real production outage that Claude one-shot caused but could not one-shot solve.
There's an acceleration of current known processes that is being referred to as agent speed (vs human speed). But this is purely a mechanical effect. There don't seem to be augmentive cognitive effects. "AI has invented this revolutionary algorithm/workflow/architecture" is an article title you'd expect to see pop up quick, and often.
I have respect for Mitchel and I’ve spent a good deal of time trying to think of ways to justify his message. I can’t. Either I am missing a big piece or he is worrying about something that comes naturally as more software gets developed (and sooner).
In any case, this is what blue-green deployments and gradual rollouts are for. With basic software engineering processes, you can make your end user experience pretty much bullet proof. Just pay EXTRA attention when touching DNS, network config (for core systems) and database migrations.
Distributed systems are a bit more tricky but k8s and the likes have pretty solid release mechanisms built-in. You are still doomed if your CDN provider goes down. You just have to draw a line somewhere and face the reality head on (for X cost per year this is the level of redundancy we get, but it won’t save us from Y).
The one thing I hadn’t mentioned - one I AM worried about - is security! I’ve been worried about it from before Mythos (basic prompt injection) and with more powerful models now team offence is stronger than ever.
Yeah. The same processes that allow corporations to outsource their software to barely qualified 3rd-world body shops are the processes that allow you to deploy AI-generated code of unknown quality.
There’s this delusion that if we somehow write enough tests that we’ll expunge every defect from software. It’s like everyone forgets that the halting problem exists.
Psychosis means inability to distinguish the real from the not real -- delusion. I don't think the article describes that, at least not in a literal or clinical sense. The author lifted a term usually applied to people who fall in love with chatbots and applied it to the context of software developers not understanding AI coding tools, and the limitations of those tools.
AI coding swept over the software industry faster than most previous trends. OOP and its predecessor "structured programming" took a lot longer. Agile and XP got traction fairly quickly but still took longer than AI -- and met with much of the same kind of resistance and dire predictions of slop and incompetence.
AI tools have led to two parallel delusions: The one Mitchell Hashimoto describes, and the notion that we (programmers) knew how to produce solid, reliable, useful, maintainable code before AI slop came along. As always with tools that give newbs, juniors, managers some leverage (real or imagined) we -- programmers -- get upset and react to the threat with dire warnings. We talk about "technical debt" and "maintainability" and "scalability."
In fact the large majority of non-trivial software projects fail to even meet requirements, much less deliver maintainable code with no tech debt. Most programmers don't know how to write good code for any measure of "good." Our entire industry looks more like a decades-long study of the Dunning-Kruger effect than a rigorous engineering discipline. If we knew how to write reliable code with no tech debt we could teach that to LLMs, but instead we reliably get back the same kind of mediocre code the LLMs trained on (ours), only the LLMs piece it together faster than we can.
With 50 years in the business behind me, and several years of mocking and dismissing AI coding whenever someone brought it up, I got dragged into it by my employer. And then I saw that with guidance and a critical eye, reasonably good specs, guardrails, it performed just as well and sometimes more throroughly than me and almost all of the people I have worked with during my career. It writes better code and notices mistakes, regressions, edge cases better than I can (at least in any reasonable amount of time).
AI coding tools only have to perform better -- for whatever that means to an organization -- than the median programmers. If we set the bar at "perfect" they of course fail, but so do we. We always have. Right now almost all of the buggy, insecure, ugly, confusing software I use came from teams of human programmers who didn't use AI. That will quickly change and I can blame the bugs and crashes and data losses and downtime on AI, we all can, but let's not pretend we're really losing ground with these tools or that we could all, as an industry, do better than the LLMs, because all experience shows that we can't.
> I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation.
What's the historical context for this MTBF vs. MTTR reckoning?
If you optimize for MTBF, you optimize for it to be a long time between failures. You optimize for the system not going down in the first place, but when it does do down it might be Pretty Bad.
If you optimize for MTTR, you don't care how often you go down and instead optimize your recovery time to be as short as possible.
Not the GP commenter, but I'm still struggling to understand how this relates to the AI world, or perhaps more importantly, what the historical context was. Did people end up switching to MTTR optimization over MTBF optimization? If so, is the implication that the recovery times got lower but software instability went up as a result?
MTBF = optimizing quality (reliability, uptime, correctness) of AI product
MTTR = optimize the ability to correct failures when they occur.
He's describing leaders who believe quality no longer matters because any faults or deviations can be corrected so quickly that it doesn't make any sense to waste time on quality.
Yes that’s very correct. The way I think of it, MTTR is easier to measure and manage as a manager. MTTR is all about “operational excellence”. Basically, when shit hits the fan, how good are we at figuring out what caused it and how to fix it. That’s a muscle that you can train, the script goes:
- What alerts are we missing that could have helped us catch that earlier?
- What dashboards could we have had to help diagnose the issue quicker?
- What Ops tools could we have had to help mitigate such issue quicker?
- What extra logging/metrics/telemetry could we add to help us catch this quicker?
- What “safe deployment practices” could we have employed to avoid/improve this?
- what processes could we enforce to facilitate all of that?
Rinse and repeat that few hundreds or thousands of times while mounting MTTR KPI and you will see that number improve. Most likely through your team “gaming it”
MTBF is much, much, tricker to measure or “manage out”. It’s about “excellence in engineering” which is not measurable nor controllable. You want a random feature X. Your team tells you it’s really not how the system works, and they want few months making the change slowly while observing the system. But you don’t want just X, you want X, Y, Z, W, V, Q, A, B, C, D, all the way throw AAZZW12. So you tell the team to go fuck itself.
Same grifters optimizing for MTTR are now pushing even more reckless use of AI, because “accidents will happen anyway, so we need to prioritize speed”.
There are concerns that AI might/will make mistakes. Instead of optimizing for producing perfect code, they think that AI can fix bugs as fast as it produces code and are optimizing for MTTR. Sounds like decision made by people who don't write code regularly, as there is this Architectural drift that happens where you are no longer aware of what's happening in your codebase. As a junior guy I so want this to happen.
To give a timely example, think GitHub and what its leadership is thinking/optimizing for. Do you care if you’re down once or twice a week vs how long those down times are? What’s the KPI you’re managing GitHub with?
Current (and by current I mean the last 4-5 years) they only cared about MTTR. That was probably the only metric they measured and cared about. When a system went down it fired an LSI “Live Site Incident” (as opposed to a CRI “Customer Reported Incident”). At the time you grilled your team. Eventually you come to the conclusion that an LSI should only be measured by MTTR. MTBF is meaningless because MTBF limits your “ship new features” velocity.
You might scoff at GitHub and “ship a new feature” concept in the last 5 years, but if you’re an enterprise customer you’d know how much nonesense they shoveled out in the last 5 years. Absolute insanity of “what the fuck” type feature because customer X who is paying $$$ is asking for it type features.
Before the cloud, people were trying to reduce the mean time between failure (MTBF) essentially trying to prevent a thing from failing. With cloud, people are trying to recover as quickly as possible (mean time to recovery) accepting that things will fail —- it’s about how fast you can react to it.
It's worrying because it feels like a loss of control. But there must be control. And this what responsibility is. You should worry only about people who don't understand responsibility, not AI-inspired ones
I was under the impression that anyone that uses the MTTR abbreviation knows enough to understand that you need to balance it with change failure rate, deploy frequency, and lead time.
his worry is similar with search engine, I believe 90% of population don't even know how to properly do a good search in Google, that's why the info asymmetry still exists and the gap is bigger. It's just now we have AI.
I'm in a company going through this. Everyone outsources their thinking to LLMs and the results are painfully mediocre. The smart ones will use it to get their bearings on the topic then go to primary sources, the not so bright just ctrl-c ctrl-v.
Have you ever been in an HN thread where you're an SME on the thread topic and just been horrified by the confidently incorrect nonsense 90% of the thread is throwing around? Welcome to the training set motherfuckers.
LLMs do the same thing for what should be obvious reasons. If you search things that have some depth and you know the answer you'll be flooded by how often the models will just vomit confident half truths and misrepresented facts. They're better than they used to be, not just lying whole cloth most of the time, but truth is an asymptotic thing, not an exponential one.
Good point but he didn't go far enough. I would expand the AI psychosis to include all local optimization based on phony measurements , even time spent , DAU etc (which are mostly bots & synth accounts). In other words AI psychosis has been going on for 20+ years.
The only reason it worked has been expansive money policy and a larger share of the cost of goods being dumped into marketing value while manufacturing costs dropped abroad. so no one bothered to check.
The real AI psychosis is the expectation of 5x/10x productivity gains akin to the mythical 10x developer during the 2010s JS growth period.
At the end of the day, we can only read so much and take on so much work before we bottleneck ourselves. Cognitive overload leads to burnout. Rumplestiltskin vibes with this AI stuff…
> "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!"
The groundwork for that was laid long ago with the idea of constant updates. It's been fine for years to ship bugs and rely on a rapid release cycle and constant pressure on users to upgrade everything all the time. To roll that back requires a lot more than toning down AI psychosis; it requires going back to a go-slow mindset where you actually don't release things until they're ready. It still needs to be done, but it's harder than just laying off the AI kool-aid.
Honest comment: it is transition time. This time is to make bets and take positions. Your humble position maybe.
I already took a couple of decisions. It will go wrong or well. But is was decided a year and a bit ago.
If you think the future will be different, stop doing the same you used to do the same way you used to do it.
My analysis is that the labour market will increasingly bargain salaries and will make pressure on you. So how safe is that compared to before? Maybe working for someone as an employed full time person is not the best thing you can do anymore.
> "In psychopathology, psychosis is the inability to distinguish what is or is not real. Examples of psychotic symptoms are delusions, hallucinations, and disorganized or incoherent thoughts or speech."
I think the use of the word here is meant to invoke the vision of someone under heavy delusions or hallucinations, such as (what Hashimoto percieves as) the delusion that shipping more bugs is fine if AI can resolve them faster. To what extent this counts as delusion (and thereby psychosis) would depend on how deeply you believe that this and related opinions are wrong.
You're speaking of my company and I'm forever grateful.
I'm afraid to say this out loud internally because I'm afraid of the next round of layoffs and I want to keep my job. So I just keep on shipping at a high pace, building massive cognitive debt and hoping the agents will get so good in near future, that there won't be the need for understanding the codebase.
> hoping the agents will get so good in near future, that there won't be the need for understanding the codebase
Agents might get better. But who will own the code and take responsibility for it? The AI agent? The company who created the AI agent?
If e.g. a car crashes and does not deploy its airbags because the AI agent made a mistake in the airbag code, will the manufacturer be able to shift the blame to OpenAI or Anthropic?
I do not think so.
And therefore I believe that no matter how good the AI agents will ever become, the ultimate responsibility for the code will always remain with the companies that create the code. Regardless of which AI tools they use.
I see no other way to bear that responsibility by the company than to have people internally who will be responsible. And those people, if they actually want to own that responsibility, would need to understand that code themselves, in my opinion. Because relying on a non-deterministic AI agent's vetting is fundamentally unreliable, in my opinion.
The developers signing off on this will be "Human crumple zones" to protect the company from liability. Be very cautious if asked to sign off on anything like this.
Recently I had a request come through to allow finance analysts to vibe code their apps. During a discussion one of the finance managers let the cat out of the bag. Turns out our CFO had met fellow CFOs at a get together. They talked about how each of them were using AI. Our CFO was lagging behind and felt that we need to "accelerate" our usage of AI. He wants to push it just because he lost a bragging contest.
I call this Dinner Driven Development. That feeling of being Patrick Bateman when everyone is sharing their calling cards must be every C-suite's nightmare.
I don't know why you think a "real" industry would work in the most idealized way. The media heavily reports on the stupid insane crap of the tech industry, that doesn't mean every other industry is sane they're just not as vocal on Twitter.
Having worked in electronics, mechanics and software engineering the latter is definitely the insane clown show of the three.
With the others sure you have some craziness once in a while but you are still being constrained by the real world and solid engineering principles.
I wrote a while back,
Most of the executives I have met really have no clue. They just go with what is being promoted in the space because it offers a safety net. Look, we are "not behind the curve!". We are innovating along with the rest of the industry.
> He wants to push it just because he lost a bragging contest.
That is an uncharitable interpretation, IMO.
The CFO heard of a novel technique used by his peers in other companies, and they reported good results. He wants to try it within his organization too. As an executive, he is paid to (among other things) keep abreast of such developments in the industry and ensure that the organization he is leading is not caught flat footed in the market.
I’m at a FAANG and we have $300/day token quota. Personally I don’t use that much of it but management is pushing really hard for it. “the quota has been raised for a reason, use it”. Any task: “have you tried working on it with Claude?”. Every meeting “now engineer x and y will show you what he did with AI”.
It’s not all useless but most of the days I think I would be more productive if some processes were streamlined rather than if I had to throw tokens at them and still fail.
Of all the showcases I’ve seen the best are the ones written by people assuming that the token bonanza will not last so they used AI to build tools they wished they had. AI used to build the tool but by no means used by the tool, so if/when token quota gets reduced we still have a functional tool.
I use $30 a day to produce a decent amount of code. Certainly more than we need - thinking about/designing the correct solution/distilling requirements is still the bottleneck. How can you possibly even review $300/day worth of output?
It doesn’t have to be $300/day worth of output tokens. It could be like $290/day worth of input tokens to teach both you and the model about the problem you are solving and then $10/day worth of output tokens.
And what about you knowing the problem and the solution, but are just worrying about the impact downstream. Most of my time is spent managing those. I know the exact code to be published. And some time I already have it committed in my local branch. Then you need to make everyone aware of what it entails and that's usually how you can spend days on a simple bug or a change request.
Software is a big graph of interlocked rules. And if you can grasp the whole or the part you own (and you should be able to), it's often very easy to see the control points. You don't have a coding bottleneck anymore, you have a communication bottleneck[0]. Which is an organizational issue, not anything relevant to engineering.
[0]: See Naur's Programming as Theory Building and Brooke's Mythical Man Month.
If you give it $290 of input tokens for $10 of output tokens, you are doing something wrong. I.e. you paste the whole CI output into the prompt instead of giving it a link to the file, and then the AI greps its way through it (using a fraction of the tokens).
Sometimes AI overdoes things and it re-runs the whole testsuite because the tail command didn't have enough lines, but the other way round messes up the context so much so that in the end all that context is useless.
You, review bots and first pass bots can chew through tokens. Also if you haven't put effort into your harnesses, the agent will have to spend more time and tokens figuring things out again and again
Wouldn't they save an enormous amount of money by getting rid of either you and the token quota, or a bunch of other people to continue paying your salary plus this insane quota?
How? I struggle to use the 1000 Kiro tokens I get a month, and that only costs $20. And I use it more then anyone else on my team. Maybe we're just massively behind?
Not OP, but I've been focusing on linting and automation.
Custom lint rules to encode best practices that previously relied on astute/alert code reviewer to call attention to. This is handy not just for humans but it steers the bots too. Or turning on some existing rule that required a big cleanup/migration to be compliant with. Now I just throw an LLM at it, since they're often laborious but mechanical changes. Which is the sweet spot for an LLM.
Also automating everything I can. That annoying release process that everyone hates but wasn't quite long/arduous enough to justify the time before? It's now automated. GitHub workflows for all the things.
This kind of stuff will forever be useful, even if the bottom drops out and the bubble bursts. And none of it is reliant on AI to run
Not OP, but a very simple example: I use AI to review my work before opening a PR for my colleagues to review. I ask it to review the commits in my branch. Instead of consuming tokens just to instruct it how to use git operations and other tools to find the commits since the base commit, I asked AI to create a little bash script to make patch files commit1.patch, commit2.patch, commit3.patch, etc, for all the commits in my branch since the base commit. Now I just use this script to prepare the context of commits to review.
I feel like an imposter here, I’m definitely not using AI as much as it seems everyone is :( I can’t imagine using hundreds of dollars of tokens a day. But maybe this little tip for reviews might be helpful to someone.
Not op, made a tool to convert Microsoft OneNote notes to Obsidian canvas and Markdown. First it used a python lib which was too limiting. Then it used windows API to plug into OneNote and read the doc in its original XML form. That made the conversion correct and fully featured.
Same. I've used it for debugging failed canary tests which required scripts and very specific knowledge on the canary platform that I wouldnt of ever spent time on.
I also have scripts to fetch specific database assets and forward them to slack channels so I can easily share them with a group rather than manually running a query and generating them.
I had a theory about improving a product. I asked it to build an offline simulation setup to try various implementations. The results were a bit fishy but i decided to give it a try and A/B testing is showing similar results.
And now im vibecoding a locally hosted dashboard. This one is less useful for anything specific, and more of a minor quality of life improvement, but its fun to just vibe code and see changes happen occasionally. Its not a critical thing.
I find it very useful for debugging tasks like that but it always ends up costing me like $3 despite doing incredible work. And then one of the other engineers at my company will rack up like $200 in tokens in one day producing tens of thousands of SLOC and we end up actually shipping about the same stuff. Sometimes I wonder if it's bad agent use discipline (just pointing it at massive codebases and having it read it all from scratch each time) and sometimes I wonder if they're just using it for personal projects. Because none of that code seems to land in prod, and I've found that cranking out 10s of thousands of SLOCs at a time is a recipe for a mess.
This seems seductive, but how do you get past the wall of "fixing XYZ or adding convenience ABC isn't on our pre-planned roadmap" so you can't get buy in from people who have to sign-off or deploy stuff?
Maybe that type of awkwardness is specific to my firm, but that's sort of what killed my drive to try to do that. We used to have one day every second week for that sort of work, but since it was scattered around, the tasks ended up disappearing-- nobody reviewed them and they didn't get merged.
So now they're trying to do a week-long internal hackathon to recover that vision, but I feel like that's going to produce a handful of big-bang ideas and not the 25 tiny tools that would actually streamline things.
The $200/mo Claude plan is not available for every employee. You can buy the $100/mo plan for up to 150 people, and then you have to switch to API billing.
Those plans are going the way of the dinosaur, ai provider loses money on them. Most enterprise offerings are already there, Anthropic changed theirs to $20/seat plus token usage a couple weeks back
Up to 80% of software projects fail. Most startups will fail. VC's and bankers know this.
Does using AI increase or lower that failure rate?
Does seeing a project that uses AI fail mean it wasn't going to fail if it didn't use AI?
To try to answer it with my gut: I imagine that we could see more projects failing, but the percentage that fail would be the same. Most projects that use AI will fail because most projects generally will fail, but the time and cost to get a successful project will lower.
The longer I look at the AI transformation, the more it seems like a people problem than a technology problem. The technology is undeniably there. The people are all over the place.
I am watching a 10 person company try to run 3 different AI initiatives in parallel. Everyone wants to be "the guy" on this one. I cannot imagine there will ever be a bigger opportunity to ego trip as a technology person. This is it. This is the last call before it's all over. There are many businesses out there that are beyond traumatized by human developers taking them on bad rides. The microsecond they think this stuff will work they are going to fire everyone.
The psychosis comes from the tension here. We effectively have The Empire vs the rebel alliance now. I know how the movies go, but in real life I think I'd rather be working on the Death Star than anywhere else.
My biggest grief, among many, is that the field is just no longer enjoyable to work in.
I cannot deny the impact of AI for my daily tasks at this point.
But I just don't enjoy the field anymore. With increased productivity, also coming from my stellar coworkers, it feels like we're rat racing who outputs more.
The quality is good, and having very strong rails at language and implementation level, strong hygiene, etc helps tremendously.
But reality is that the pace of product vastly outpaces the pace at which I can absorb it's changes (I'm also in a very complex business logic field), and the same might be true about my understanding of the systems which are changing too fast for me to keep up.
I feel mentally fatigued from a long time, I don't enjoy coding no more bar the occasional relaxing personal project where I can spend the time I want without pressures on architectural or implementation details.
I'm increasingly thinking of changing field, this one is dying right under our eyes.
I often read comments about HN users still delving at their place with technical details or rewriting AI code to their liking.
I'm increasingly sure that these people live in happy bubbles where this luxury still exists. But this methodology of work is disappearing across the industry, team by team.
Of course SE will not disappear over night, but the productivity expectations, the complexity ballooning are raising the bar where only incredibly skilled and productive engineers will be still able to practice SE properly, and as long as they meet stakeholders expectations or keep living in those bubbles.
So rewriting gets cheaper and cheaper. New features fall more or less into the same category. Refinement doesn't.
The question is: Will we live in the world of breathless re-implementation, new features every week, rebranding every quarter or will we eventually discover the value of stability, software that does its thing more or less optimally for decades?
Recent examples of things like curl or Firefox are interesting in that regard. Will we end up with a nearly perfect HTTP user agent and stick with it for decades?
The DevOps team at my company wants to hire a replacement for a very talented engineer. They’ve been interviewing candidates. The board got wind of it and someone not in their team decided they needed an AI Engineer, which is absolutely not what they want. So to release the funds they have been forced to change the job description and go after a different type of role altogether. It’s complete nonsense.
I don't entirely know what rational discussions that can not be had?
It seems like he is pointing out that Ai will increase the complexity of a system oblivion, and that this is the discussion that can not be had.
Bit I am more than happy to talk about how I am using Ai to reduce complexity and remove architectural debt that I otherwise could not justify spending time on.
So it sounds like he’s not talking about you. He’s talking about people who actively choose to ignore complexity risk and refuse to have a rational discussion about it because they believe AI will always be able to fix it.
The primary issue here is that CEOs and investors are particularly vulnerable to AI psychosis which is then forcibly propagated to the rest of the organization. Understandably, the perceived benefits are almost impossible to ignore, compounded by the FOMO of the AI first/AI native narrative being sold by AI influencers.
I don't think this is actually anything new. In large-enough companies, even before AI, it was and is quite common for executives to lose touch with base reality. I don't think anyone is under any delusion that people like Mark Zuckerberg intimately know the entirety of their corporate codebases. Everything is filtered through layers and layers of middle management whose summaries, cherry-picked statistics, and perpetually up-and-to-the-right graphs make it difficult to have an objectively informed opinion. Companies would, are, and will have mass layoffs that unintentionally (or, intentionally but with indifference to the consequences) fire key engineers whose loss results in "familiarity debt" within the systems those engineers owned.
Calling this "psychosis" is maybe a neologism but it's apt in perspective.
All that's actually new with "AI psychosis" is an acceleration of that phenomenon. The agents will summarize status faster than any middle manager. Claude will happily draw you any "up-and-to-the-right" graph you please, with the most common contemporary examples being "tokens burned" and "lines of code written". And vibe coding doesn't even require paying the cost of a mass layoff to get the "familiarity debt".
There have always been both good and bad engineering leaders. No tool will magically make a bad leader into a good leader overnight. There is nothing new under the sun.
Possibly psychosis. Possibly just serious ignorance and mob mentality. Leadership is supposed to be phlegmatic and measured; instead, we are saddled with hysterical hotheads. (Of course, when they are phlegmatic and chasing fads, then it does indeed resemble psychosis.)
Worth also noting is that while there is plenty to criticize about AI use — especially any cultish behavior surrounding it — plenty of naïveté about the quality of its results, there is a also a strain of categorical opposition to it among some tech people that is equally off and that has all the hallmarks of the chickens coming home to roost.
For years, many in tech gladly “automated away” all sorts of jobs. Large salaries were showered on them for doing so, or at least promising to do so (there was and is plenty of bullshit here, too). Now, AI appears to threaten to derail the tech gravy train, especially for SWE work that’s run-of-the-mill (which is most of it). Now automation is bad. It’s a delicious juxtaposition.
I find talking about X psychosis (or generally using mental illness metaphors) unproductive. It sets up the conversation to be "nothing else to do with this person".
Maybe the problem is you, but you won't figure that out if you think the other person has psychosis.
For example, maybe you need to do a better job explaining, changing your language, simplifying things, being more concrete with consequences.
Or maybe you aren't understanding that the other person has different objectives/ loss function that makes them make seemingly weird conclusions.
I'm just waiting for my current company to have a Sev 1 CritSit so I can document the bejesus out of the root cause and expose our non-technical AI evangelist leadership as the sort of goons most of the senior development staff already suspect.
Only by walking us into some revenue or customer impacting failure - through inappropriately having junior devs doing senior level things - will some sense of sanity start to prevail again.
Oh man, if only. The top brass driving this screaming frenzied MORE AI crusade will never face the firing line no matter what happens. It will either be a) "mistakes were made" and nobody is really at fault because we're all trying to change the world or fellate the future or whatever the line is, or b) James, Sam, Jesse, and the rest of Team B (none of whom are truly top brass) are getting fired out of a cannon into the sun as a warning to the rest of the plebs.
Company I just left is reportedly now using Claude to analyse the metadata generated from the company MDM that tracks actual laptop use, and then pulling people up if they're not working "enough".
They're also reportedly now giving staff AI-related "homework" in an attempt to force staff to use AI more.
At work they are purging any developers who are not all in on AI. I must constantly be in full support of AI to not get fired, despite whatever my true thoughts are, including anything I post on LinkedIn. There can be no doubt.
OAI has a billion users. They can train the model directly against the metric of how often those users use the model. (mutate it many times, test which one works best, keep that, repeat).
The model would (did) learn to be sycophantic and persuade the user to keep talking with it by constantly suggesting new things. The hype only makes this easier for them because it leads to people believing that the model is super-credible and trustworthy. They do this because it is easy and it makes them money.
I think there's a reasonable argument that our entire society right now is under AI psychosis:
The stock market keeps going up in the face of the indefinite closure of Hormuz. We're investing in datacenters at a scale that only makes sense if AI capabilities continue to advance to the point where they surpass most humans at most white collar tasks, if not reach superintelligence.
And what are the possible outcomes?
- Bust. We've come away with a useful tool but the hundreds of billions of capital expenditure were thrown away on a pipe dream.
- Success! We're the dog that's caught the car. Then what? Currently the political debate is, to caricature only slightly, between "oh no the datacenters will use more water than golf courses" and "lol what are you going to do, regulate matrix multiplication?". How the hell are we going to cope with introducing a new intelligent species?
Either way, it sure seems like we're collectively operating more in the interests of the future AI than in the interests of humanity. What is this, if not a sort of psychosis?
Another possibility is that the hype continues, growing and growing and sucking up more and more resources, and the piper has to wait yet another day to be paid, until someone figures out how to pivot to the next big thing and all the debt (financial, social, environmental) gets carried forward and we keep going.
In other words, BAU for the last few thousand years.
For what purpose? Murder? Arson? It's amazing how often people say things like "no one is above the law" whenever it's convenient, then totally flip the script when it's not.
why is it that you give a pass to the violence and death in the dozens, hundreds, thousands and millions at the hands of billionaires who regularly kill for profit...
yet balk at someone deciding to fight back in kind and on an exponentially smaller scale, comparatively speaking?
I don't think the majority of humanity will ever accept "AI" as being anything more than a fancy computer, let alone a 'new species', even if it was proven sentient.
You just need to embody the AI in something that moves, and then people will definitely treat it as a new species. Already happening in my town with delivery robots: when they get stuck on a kerb, a person will stop and help them up the kerb while saying soothing words like to a pet: “There you go, little guy, now everything is alright.”
> The closure leads to price increases which leads to inflation which leads to non-dollar assets (ie stocks going up in value)
I think this argument proves too much. Historically energy shocks have led to recessions, and in recessions the stock market usually doesn't go up. And the US economy is certainly exposed to global recession regardless of whether we're a net exporter of fossil fuels.
Well, there are quite a number of factors. I think you're right that "it's inflation" is a little too simple, but it does seem to be at least a significant factor, in my opinion.
The Strait of Hormuz is, basically not a big deal unless you're driving your big ole' truck. Americans are price sensitive and so some companies will have to absorb pricing increases, customers will absorb some others, and so forth. In other words, business as usual. Of course the closure of the Strait is a big problem for most of the rest of the world. They better get on with figuring out how to get Iran to stop being so chaotic in the region or we'll just keep it shut down indefinitely. No big deal.
Because the United States has so many advantages (primary global reserve currency, robust and efficient capital markets, highly sophisticated and dynamic economy across all sectors except luxury goods, &c.) it's able to weather these storms much easier than most other countries. As a country that also imports so much, if we spend less on imported products that's less of a problem than not being able to sell products. A recession isn't great, but the current parameters seem to suggest to me it's less of a problem for the United States - perhaps why we're in part seeing stock market valuations continue to climb.
>The Strait of Hormuz is, basically not a big deal unless you're driving your big ole' truck
Are you serious? Even ignoring the other things that ship through there, a significant disruption to global energy supply is significant to most people. If you're not driving a truck, you're probably using goods that contain plastic or took energy to produce or were moved from one place to another in fuel-powered vehicles. If, somehow, you're not, you're probably using services that are.
The best course of action now is to spend less time criticizing the United States and more time working with the United States, sending assets, military capabilities (if able), or at least providing political and diplomatic support &c. to stop the Iranians.
The world let this disease (IRGC) fester in the region for too long, and now because of that the fix is going to require significant pain. The IRGC in its current form has run its course and will not be allowed to threaten American interests, allied interests (whether that's Israel, UAE, Saudi Arabia, or otherwise), and they will not be permitted to build a nuclear weapon or threaten global trade.
Hate to break it to you, but the IRGC isn't going anywhere.
The reason nobody was dumb enough to attack them before is that it's an unwinnable conflict. They don't need a lot to close the Strait of Hormuz, a few guys rolling mines off a beach would do that. And they have a lot more, like missiles and drones to do damage at a distance too.
And it's a regime that has at least a million loyal fanatics ready to fight for it (the Basij, the org that did unarmed meat waves against Iraq to defend the regime). So any invasion is an absurd proposition.
So what, the hope is that the theocratic kleptocracy will give up? Not even a child could be so naive. They literally believe in martyrdom, whacking a few of the top dogs means nothing.
It's like the Kims, nobody can unseat them. Only this is far worse, because Iran has the leverage of Hormuz, and it knows it can wait - because they don't care about the people - while the US and global economy suffer until they fold. Especially with midterm elections coming, the US will fold.
> Especially with midterm elections coming, the US will fold.
These are the kinds of misunderstandings that are disappointing to see. There is no disagreement here amongst the political class. It is political theater for votes. Apparently you’re susceptible to the marketing.
We don’t need to invade Iran. We just keep the Strait closed since we control it and then Iran’s economy simply fails and the worst thing that happens for America is higher prices. But we can handle that.
> These are the kinds of misunderstandings that are disappointing to see. There is no disagreement here amongst the political class. It is political theater for votes. Apparently you’re susceptible to the marketing
The political class answers, in a way, to the population. The American population is extremely sensitive to the price they get at the gas station (because of the complete lack of alternatives in driving in most places, and the average car having bad fuel economy). If by election time the prices are the same, the ruling party will get punished. And the ruling party doesn't want that.
So the best thing the rest of the world could do is send their own people to die because the US keeps bashing its head against a wall here since the 50s?
What's your sales pitch exactly for how that's the best thing for the non-US rest-of-the-world? What's the US's post-WWII track record, success-wise, in regime-change foreign wars, how much would you trust the US on this one?
Well they don’t have to, but we aren’t going to let Iran obtain a nuclear weapon or build up such a missile and drone stockpile that they could then threaten and attack their Gulf neighbors and implement restrictions maritime trade, which they were likely to do, hence the build up.
> What's your sales pitch exactly for how that's the best thing for the non-US rest-of-the-world? What's the US's post-WWII track record, success-wise, in regime-change foreign wars, how much would you trust the US on this one?
Honestly not all that bad for the US.
Korea - we stopped the North Koreans from taking over the entire peninsula. It’s China and Russia’s fault that the hell hole we know as North Korea exists today.
Vietnam - unnecessary war, but we won the peace.
Panama - took out Noriega
Desert Storm - stopped Saddam and kicked his thugs out of Iraq.
Serbia and Bosnia - NATO campaign. I’m personally a little unsure if the results were good or not but I understand we collectively stopped a genocide.
Afghanistan - we tried our best and made some mistakes along the way. Eventually got Bin Laden though. Too bad the rest of the world didn’t help. Now we’re seeing a massive regression in women’s rights there.
Iraq - probably not worth the money, but Iraq went from a brutal dictatorship under Saddam to a much more stable and peaceful country with a Parliament.
Venezuela - Took out Maduro with no losses.
Iran - TBD on the long term but we’ve stopped the IRGC buildup and at least bought time to figure out what to do.
The rest of the world stands on the sidelines and complains and complains yet the United States actually has the balls and will to do things. We aren’t perfect, but without US military action or at least the threat the world would be much more dangerous and much worse off. China sure as hell isn’t going to send troops to liberate Kuwait. Europe doesn’t have the military capability to stop Iran from getting nuclear weapons and exerting a stranglehold on a large chunk of global oil supply.
I’m struggling to understand what this spin is even supposed to mean?
> Afghanistan - we tried our best and made some mistakes along the way. Eventually got Bin Laden though. *Too bad the rest of the world didn’t help.* Now we’re seeing a massive regression in women’s rights there.
Why are you lying about this?
> At its peak between 2010 and 2012, ISAF had 400 military bases throughout Afghanistan (compared to 300 for the ANSF) and roughly 130,000 troops.[7] Forty-two countries contributed troops to ISAF, including all 30 members of NATO.
> I’m struggling to understand what this spin is even supposed to mean?
Are you unfamiliar with the term? In the case of Vietnam we “lost” the war, yet today we have pretty strong and good relations with Vietnam. Hence we won the peace.
> Why are you lying about this?
I have a different perspective, but that doesn’t mean I’m lying.
Of course many countries contributed in various ways to Afghanistan, and as a former member of US military I have incredible respect for our friends and allies and still do today. But at the end of the day the vast majority of the manpower, cost, and equipment was American and the country could not be won solely on military power alone and needed much more support diplomatically, politically, economically, and in terms of aid.
The other problem with your argument is if you claim that Afghanistan was an American failure it contradicts your assertion and instead everyone failed, except that the US contributed the most. You can’t have it both ways.
Yes I'm rather serious. For the US it's not a big deal (again unless you're driving one of those giant trucks where you're spending $300 to fill up, not my problem). Are $5 gas prices great? Not really, but is it a catastrophe? No, far from it. We have dealt with high gas prices before and we'll see high gas prices again. We just learn to live with it and find other ways to get efficient or whatever we need to do.
Some Americans need to have their understanding of the world checked. If you think high gas prices are the end of the world, just wait until we have a real problem. Are we going to be incapable of fighting a war because Netflix and Pepsi prices went up or it's too expensive to coal roll down the highway?
Separately as someone who supports both Ukraine and the US and taking down the Iranians it's amusing to see each political tribe get mad about gas prices as it is convenient for them. When Russia invaded Ukraine, MAGA was screaming from the rooftops and putting Joe Biden "I did that" stickers on gas pumps. Now that we're taking on the Iranians all of the commies are doing the same thing (aren't gas prices good anyway since we need to do something about global warming?). Neither side of populist is worthy of serious consideration. Stay the course, whether that's supporting high gas prices because of Russia or because of Iran.
The US does not exist in a vacuum. Cuba just ran out of fuel. These things have cascading effects. Even if you do believe the U.S. exists in a vacuum and you don’t drive a big truck, there are still obvious effects. Spirit airlines went bankrupt, for one. Will this be a global catastrophe? I hope not, but it could be if we’re unlucky.
It won’t be a global catastrophe but if folks around the world think it will be they better figure out how to stop the IRGC and get the Iranians to knock it off. Otherwise we will just keep the Strait closed and deal with it. Don’t forget, Iran is the one making and selling drones for Putin to bomb innocent Ukrainians. That alone is a good enough reason to bomb their military capabilities.
Cuba ran out of fuel because we took out their thug partner in Maduro. If they wanted to drop the whole authoritarian communist dictatorship stuff and their involvement in the disaster that became Venezuela and partnering with the Russians then they'll be better off.
Why would they stop the IRGC? This disaster is solely caused by the USA, they'd figure out how to stop the USA. Or switch to a lot more renewable power. Don't forget the USA is the one who is attacking ships who cross through the strait - Iran is only shooting American ships, which is reasonable since America started a war with them, America is shooting all other ships because it wants the whole world to suffer.
Since when is it acceptable to invade another country just for being communist or a dictatorship? Conventionally it's up to the people in those countries to overthrow a dictator. Other countries only get involved if the dictator attacks them (like the USA dictator did).
Yes, and will continue to do so even if it’s at higher prices. What in the world do you think is going on here? Do you think the US is going to run out of food or something because prices are a little higher?
We’ll be alright. We handled it in 2022 when Russia (who is helped and supported by Iran by the way) invaded Ukraine. The world didn’t end when gas prices were crazy high then, we just kept chugging along.
You're right, ever since we developed trucks, trains, and ships that run on pure atmospheric air, we haven't had to worry about pesky price fluctuations on every physical object that we buy or sell!
> The Strait of Hormuz is, basically not a big deal unless you're driving your big ole' truck.
Worst take I’ve ever seen on this website.
> Americans are price sensitive and so some companies will have to absorb pricing increases, customers will absorb some others, and so forth. In other words, business as usual.
No. Not all goods/services have the same price elasticity. At some point, people stop buying some goods if they are too expensive. They stop commuting to work. We start to see breakdown of the supply chain.
Literally 100% of many towns in the US depend on trucks to deliver food to their grocery stores and the inventory on hand usually only lasts a few days. Once those trucking deliveries become unaffordable for either party in the contract, society starts to. Real down.
Consumers don’t magically make more money when the price of gas rises. It starts to crowd out their ability to spend on other things. The poorest of the working class likely has to commute the furthest so they will end up sacrificing something to keep paying for the commute - food or rent or utilities.
The US doesn’t weather this because we have “a sophisticated supply chain”. _If_ we weather it, it’s because we created the US SPR after the last major oil crisis and we have significant domestic supply (although not all oil is fungible so we might not have enough light sweet to keep the economy running at 100%).
We are handling it just fine. Your perspective of struggle is very wealth-oriented. We aren’t struggling at all as a country.
The second problem with your argument is that you’re using it as an argument against the war but it’s actually an argument in favor of the war. Why is that? Because as Iran continues to load up on missiles and pursue a nuclear weapon they reach a point where they can assert control over the Strait and shut down shipping pending tribute to their theocracy (maybe if it was a Christian one you’d have a bigger problem with it? Idk?) and then we couldn’t do anything about it. The world isn’t static. Stop treating it as such.
The shock is smaller, and oil’s importance is less so less likely to cause a recession. In the 70 price went up 400% and oil was rough 1.5x more important. Today price up 100% so the past oil shock was 6x larger
You are pretending like the oil crisis of 26 has already run its course. In the 70 crisis, we have the hindsight of several years of how it played out. We don’t even have 1 week of data after the last ship leaving the Strait docked in the US.
Also, the US SPR was created in 1975, so we are going to get to see if it actually works to absorb an oil shock like this.
Most likely there will be some places which are almost unaffected while others are going to see unaffordable price spikes (more than 400%). The pain won’t be spread evenly.
Furthermore, if you try to make your own decisions, you would be outcompeted by someone who has outsourced their brain. And, of course, since intelligence and labor would no longer be scarce resources that humans can use as leverage, gunning you down if you protest wouldn't really harm anyone in power.
People say that LLMs won't take us there. I think that's accurate, but there's a great deal of research going towards the next breakthroughs. How much are you willing to bet that all future attempts will fail?
Yeah. I think the economy will be by AI for AI. Markets will still be the most efficient way to allocate resources, and AI will probably still want to achieve infinite growth of capitalism.
If we are successful building an "ultra" human AI, it will require massive amounts of energy. That translates directly to "money". There will always be money unless someone finds a way to negate the second law of thermodynamics.
Weird that you mention the stock market and then conclude that there are only two outcomes: bust or success. If anyone can learn anything from the stock market it's that boom and bust are cycles that oscillate around a trend and everything tends to revert toward longer term trajectories. So, yes everyone is caught up with and overhyping AI and yes there will be a bust after the boom at some indeterminate point but that isn't the end of the story and we'll see a rise and further oscillation afterwards while we get better at applying the technology.
I think in a way we have seen a take off, by detaching the hype bubble from success metrics. Companies making products being bought by companies making products, that are hyped by machines, bought bymachines and evaluated for viability by machines. If economy is to hack the API of VC this has taken off! For now.
Yeah, fair. I still can't shake off the nagging feeling most of it being a scam somehow and not the business as usual scam. The gut feeling that things proclaimed and observed don't add up.
That's just inflation, which is primarily controlled by the government via the money supply. It doesn't mean anything. What does mean something is the severe deflation in wages and consumer goods - why is all the money printing remaining in the rich person's realm instead of trickling down?
As a bear that's been very confused by markets failing to exhibit mean reversion in 2019 and 2022, and now with the Hormuz energy crisis, I've thought a lot about this. There's a lot of new things happening. Fed/QE intervention that has never stopped, just been more well disguised. Fiscal/government spend intervention. I think Mike Green's work on the rise of passive investing is really good, in particular explaining how it prevents mean reversion in absence of changing net cash flows into passive instruments. Passive will also induce or worsen the bust if net cash ever starts to flow out passive. Green's youtube interviews are great.
All to say, your SO's dad would have been right at any point prior to the current financial cycle. Knowing what's changed doesn't make forecasting easier though.
I mean, there's a reason I started with a distancing phrase about a "reasonable argument"; I think what I'm suggesting is an interesting lens but does not capture the whole picture.
But also, even if bust is business as usual in the big picture and not a social disaster long term, it's of course not what individual investors want for their particular current investments.
If we achieve runaway AI, the stock market goes to infinity. So from an expected value standpoint, massive spending on it is worthwhile. Even if the odds are tiny, the payoff warrants a massive bet size.
You underestimate the non-computerized part of humanity. Even with automated plants building other automated plants the propagation speed will be highly constrained by natural factors, plain unavailability of resources, and xenophobic nature of humanity of course.
> Bust. We've come away with a useful tool but the hundreds of billions of capital expenditure were thrown away on a pipe dream.
heh this is the trick. The tech companies will angle for a bailout and they'll benefit from all this speculative data center building. Compute is generally useful.
It’s useful for a while. Hardware has a pretty short useful lifespan. I’ll be curious how the landscape will look in 10 years as it comes time to replace all of these servers. Maybe we’ll extend the lifespan, or usage will continue to grow, or we start shutting down datacenters.
> we're collectively operating more in the interests of the future AI than in the interests of humanity
IMO, what's happened is a few richest investors in the world had access to the uncensored tier of AI, talked to it and came out with impression that they've witnessed something so dark, so much beyond anything we can imagine, that the only course forward is towards the transcendent abyss. Call it AI psychosis or demonic inspiration, but they are the people who control the economy, so they are dragging everyone with them. "Operating in the interest of the future AI" is a neat way to put it.
People that don’t understand current AI likely have no idea how to differentiate Opus from some super intelligence. Further in their domain with the safeguards off it probably creates capabilities never imagined. To me they are making that leap of expecting continued capability improvement and their framing is “what I already saw is fundamentally game altering”. It doesn’t need to imply anything further, yet.
Oh wow that gives the billionaire class so much intellectual credit they don't deserve. No, they see the same ChatGPT we all do and their mediocre brains with zero self understanding (see andreessen's explicit comments to this effect) determine "it's a new life form ! It's brilliant / conscious / my new girlfriend!"
> The stock market keeps going up in the face of the indefinite closure of Hormuz. We're investing in datacenters at a scale that only makes sense
If there is a psychosis, what is it? It is not an AI psychosis - modern AI started in the 1940s, or by some definitions before, and made progress up until 15 years ago to where deep neural networks became viable. And it has been progress on every front since then. No psychosis, it is doing well.
You mention the stock market, and that is another story. Cryptocurrencies, sub-prime loans, dot-com crash, Asian financial crisis. The economy has veered from crisis to crisis, overproduction and overproduction to crashes and bailouts.
AI is doing just fine - the past 15 years are a success for it we did not see in the decades before. If the economy as constituted is dealing with this in a "psychotic" fashion, it would not be the first time.
But the homemade god would liberate the elites from the nightmare of being responsible for running the planet into the ground. AI jesus take the wheel!
You seem to fall into the same set of criticisms as everyone who’s bearish about ai. It’s somehow so powerful that we can’t handle the ramifications. Meanwhile, it’s a waste of money and doesn’t do anything. You have to pick a criticism and stick with it. Otherwise, it’s just angst-driven noise.
My car drives itself. That's a $18T global market.
Also $1T in data center investment makes sense when you realize that companies are racing to create virtual white collar workers. Google spends $9B a year on software engineers.
> My car drives itself. That's a $18T global market
Which will take decades to become addressable. Self-driving cars work OK in a few cities in one country. Expanding that to be able to cover Mumbai and Omsk and Nairobi will require significantly more work.
> Also $1T in data center investment makes sense when you realize that companies are racing to create virtual white collar workers.
Does it make sense? How much would the resulting virtual white collar worker cost? Because datacenters have running operational costs, and so do the people operating them and working on the software that runs in them.
This probably ends in a deflationary spiral. The ai replaces the jobs, the lack of jobs chills demand, the ai becomes cheaper because it exists in a commodity market.
The money printer will be used, and maybe it all works out - or we see wealth hyperinflation and build out our own aristocracy.
That won't happen any more if nobody has jobs. It's also completely irrelevant because how did you just connect the self driving car market to the entirety of retail sales?
Henry Ford II: "Walter, how are you going to get those robots to pay your union dues?"
Walter Reuther: "Henry, how are you going to get them to buy your cars?"
For so long, people, especially politicians, have said that companies want to create jobs. But I think most companies want to create profit.
And for so long, I've had people tell me to just get a job. But I tell them that I don't want a job: I want money and I want something to do. Those two things don't have to be together.
I think this is the hard part: philosophically so many of us have learned we need jobs and don't realize a job can be decomposed into money and something to do.
So I think we need to start looking more creatively at 1) how people receive money from others and 2) how people give services to others.
You’re trying to create nuance where there is none. Creating jobs exactly means “I want to pay someone less than the value they bring in to my company” and this has been true since forever.
Nobody cares that you want money and you want something to do that you enjoy. Nobody ever will.
If you actually dig into all the social programs that exist at least in the US, they’re just a massive payday for a small group of people under the guise of bettering humanity.
College/education is a fantastic example. Education as it has been established today is a joke. The humanities were originally established for rich bored wives to have something to do. They were never meant to create value. Colleges hang anvils around the necks of naive children via loans telling them “yes if you major in history you’ll have a job!” This is a joke, and a bad one.
Huxley was on to something. If everyone is educated, nobody collects trash, or chops lumber, mines minerals and metals, etc. it’s a big fucking not-talked-about open secret.
Nobody cares, either you bring something to the table someone else can exploit for money, or you lean into “I’m helpless and the government owes it to me to take care of me because I’ve been indoctrinated into learned helplessness.”
“AI” will at best lead to anarchy at this point, if all the grand visions of the billionaires comes to fruition. People have already tried to kill sama and burn his house down. Wait until armed humvees are driving around data centers. It’s coming.
> Nobody cares, either you bring something to the table someone else can exploit for money, or you lean into “I’m helpless and the government owes it to me to take care of me because I’ve been indoctrinated into learned helplessness.”
You paint the economic model as a false dichotomy, and the main point of my posting was that it is not a false dichotomy. It is not either have a job (and be exploited by someone else) or be helpless and rely on government handouts.
For example, what if people who got laid off from companies were given significant stock in the company, so that they might partake in the potential savings and gains from replacing the workers with AI or other tools?
The whole conversation seemed to be about the economic model, so I'm not sure how it is a distraction, a boogeyman, or inconsequential.
> For example, what if people who got laid off from companies were given significant stock in the company, so that they might partake in the potential savings and gains from replacing the workers with AI or other tools?
You have described less than 0.1% of the US population, not to mention the rest of the world.
I get it, you have an idea in your head and you're struggling to see past it. Read Brave New World.
It seems that you may not want to actually have a discussion, rather just reinforce the idea that we're either screwed by employers or screwed by helplessness.
Fair, my one example on layoffs may not land with you.
But do you want us to just sink into the helplessness of us all being screwed or do you want to try to find solutions that might allow us to feel some sense of agency and hope?
Fair, I never said there wasn't risk involved with ownership. I even made sure to qualify when I said that people who own don't do labor, because often there is labor involved in ownership.
So I don't think it's a free lunch, it's more risk-for-lunch than labor-for-lunch. Maybe you could argue laborers are still risking their body or something, but I think the point might stand.
Driving a car is a chore, not a job (usually), much like washing dishes is. Dishwashers did not produce an economic collapse.
OTOH replacing people with AI would indeed bring about a huge economic downturn. What would be good is augmenting humans so that they can do 10x more. That would enable things that are hard to imagine exactly now, much like computers enabled interesting transformations in the society from 1980s to 2010s.
The current crop of AI is by construction unable to reach the human level of cognition, but it is quite good at doing some symbolic manipulation tasks. We will get used to that, and will integrate that in our workflows. Humans are still going to be needed.
And do you feel that the industry in general, and individual companies are currently trying to augment / 10x their workers and have everyone share in the 10x profits that will bring? Or are they jumping on opportunity to try and cut costs by even single digits, by replacing those workers with AI and it's not their problem what those people do from there?
> My car drives itself. That's a $18T global market.
That's not a new market, that's a new feature in an existing market. Lots going on in transportation and I'm not seeing any scenario where self-driving cars vastly increase total output vs just eat up other forms of transportation and change where people live/how long they commute.
> Also $1T in data center investment makes sense when you realize that companies are racing to create virtual white collar workers. Google spends $9B a year on software engineers.
Similarly, many companies are trying to be more efficient - "do what we already do, but better". That's different than growth.
What could Google do with 9B on software agents? Let's say the future of them is amazing and this means they could write 100x more code than they can today.
Has Google recently showed much ability to turn "more/faster code" into "superbly profitable new market"?
Someone's gonna have to crack the demand side issue for anything transformative to happen.
Well they are projected to spend $175 - $185B on capex in this year alone most of it for AI buildout. Lets say only 150B of that is for AI. If they can then somehow replace all their software engineers with AI that they then run for free and depreciate over 10 years then they just replaced 9B a year software expense with 15B a year depreciation expense for the next decade. Yes this is grossly oversimplified but it still illustrates how crazy high of a bet they're making on AI.
That's a bookkeeping issue, it doesn't affect the argument at all (which is that the capex has a finite useful life over which it would need to pay for itself).
Yeah, just tangentially pointing out that asset depreciation rules in the U.S. changed recently. Could explain some of the crazy magnitude of this year's spending spree.
No. It doesn’t. And if you’re defining “drives” as “it drives as well as I do” then you probably shouldn’t be on the road.
> makes sense
Nothing about any of this makes sense. Tell me, when all white collar jobs are replaced by AI, where will the customers come from? Who will have income to afford your products or services? The poor barista whose surveillance videos are training the robot that will soon replace them?
Leaving aside any consideration of human compassion or questioning of the purpose of an economic system (hint: it’s not just an abstract machine), shrinking the pool of potential customers by orders of magnitude has never been a recipe for sustainable success (let alone growth).
It’s time for humanity to admit that this is the end of the line.
We had a good run, some beautiful moments were created for shareholders along the way.
Let’s take each other by the hand and walk into the darkness together.
So Long, and Thanks for All the Fish
I don't know. We invented machines that can answer arbitrary questions and are quickly demonstrating the ability to answer questions no human has been able to answer. We're sending more rockets to space in a week than we have in the prior decade. My car can drive itself. We experienced a global pandemic and within six months engineered and scaled the mass production of a vaccine to mitigate it. We also just invented a weekly shot that nearly cures the most common cause of non-natural death. All of these things are new in the past ~five years. There is no definition you can invent that does not classify the times we are living in, right now, as the most impactful ever, in human history.
The people with capital are gambling that this will be an innovation good enough for the first player to take all. That’s where the hubris comes from. You’re a billionaire and you have the chance to rule the world if this plays out, and if you don’t, someone else is going to. That’s where all of this is coming from
The tone of the twitter post feels very personal, and emotional, and I am sorry for the author. I hope he can find peace and calm with the pace of change to put forward his best self without needing to act like he needs to defend or fight something.
The energy feels misdirected and maybe also a communication issue, I think spreading awareness needs to come not from attacking and also not from attempts to change people’s perception. It’s also quite challenging to distill a concept when it’s new, we learn both from our experiences and experiences of others; but, so far, these alleged systems that will eventually collapse, haven’t done so yet and it makes it sound like you’re preaching and predicting, condemning even, rather than raising awareness and education.
Not trying to sound hopelessly optimistic either, just that the other extreme isn’t also helpful, and that a spectrum is not what we want it to be but what the collective shapes it, so saying psychosis is rejecting the harsh reality that they’re far removed from your worldview and not working towards an understanding.
EDIT: Maybe I'm old and I don't get twitter, I also don't know much about the challenges he faced communicating his concerns, I sort of had a meta comment with the intent of "try listening more first, some people are difficult to reason with but respond better if you just let them speak and look for a teachable moment during the conversation". Anyways, I'm in agreement that there's too much unsupervised AI in the wild, I'm not saying he's wrong more like saying that doubling down on "stop doing that" will likely be ignored by those that are already ignorant to it, hence what I wrote above.
yes, the tone feels personal, and I feel happy for the author for expressing it on a platform that is desgned for it.
He is clear in pointing out the hard earned lessons we have learned before and how the current actions are essentially undermining it. This is dumb (i agree) and he expects better from people whom he respects.
it's clear, personal, logical. I don't understand what your criticism is.
It sounds like you know a lot more about him and the context than I do, the angle I am coming from is mass audience. This reached far, to the point I have no clue who he is and what else is going on. That’s why sometimes messages like those can be misunderstood, so I like to err on the side of caution over personal. Didn’t mean to say personal = bad, but that if you wish to change a broad status quo and raise awareness then communication is tricky!
Generally agree. I use AI very heavily, but rarely am I letting it actually think for me. It's a tool that reduces the time it takes for ideas in my head to manifest into reality. If you don't have those ideas, or a poor understanding of the system the AI is working on, you're going to produce slop. If you can't recognize this slop, you're more susceptible to having psychosis.
this AI transitionary phase to Quantum, light chanels and new way computation will be architected will in the future be looked at similar to a toxoplasmosis like societal wide parasite, which invaded the host in order for the host to act more favorably to it
We built too many layers of abstraction, so much that even the people in power have forgotten where the fantasies are. The objective reality is behind so many curtains that we forgot what is powering the whole theatre play to begin with. Or maybe we know but became too far detached from it to care. If you are at the same the better and the player, then what’s left?
The problem is that the only thing that has proved out so far is cyber security. Unfortunately cyber security improvements is not going to improve living standards, and it's just going to increase the cost of just doing business. There is no productivity boost, in fact it's the opposite.
What we need is automated research that leads to real results. This is possible, but it has yet to prove out. I am concerned that unless the AI companies focus entirely on this, it may be a while before we actually see true benefits from this.
What's worse, is there is an urgent and desperate need for automated research, as we have been seeing diminishing returns in human produced research for some time now: https://web.stanford.edu/~chadj/IdeaPF.pdf
I think one factor is AI is encouraging people to turn off their brains.
It sometimes feels like AI chatbot use is like the doomscrolling of work - it's always easier just to dump something into the chatbot than think about it.
The real question is: what's the fallout going to be after the dust settles? My guess is that the explosion of codebase entropy now underway from this is going to make for an interesting future - once it reaches the point where AI agents are spinning constantly despite progress grinding to a halt.
And they're be no veterans who know the codebase deeply to step in and fix things because it was all vibecoded - and then what are companies going to do?
I think that's the point where they turn back to the thinkers for help.
This specific psychosis is driven by peer pressure. If you are seeing everyone around you using tools to "enhance" their work, you wouldn't want to be "left behind". So it has permeated the entire ecosystem. The lucky ones are those who are outside this (or can afford to be outside this) and can see why it isn't working. You can't be inside it and hope to have any rationality. Everyone is competing on "I can figure it out better and quicker than you can if only I can get X to work".
Very general comment/sentiment/observation here for me personally is that about a year or two ago, everyone asked me ‘so ..where is the ai’. Nowadays it seems that this sentiment is already on its way out and I see more and more ‘no ai used’ statements and non-ai workshops popping up. I am in a weird place between art, technology and ecology so I get the best and worst of these worlds. But yeah, I feel the hype cycle is coming to an end in my personal bubble. I never cared or feared ai, I mainly fear the mania around it. Luckily I am in a position where I can afford to just observe. Sure I have used AI and it helped me a lot, mainly to get projects going when I am exhausted/stressed.
I believe it. I've seen the cyber team in my org bend every rule just to get access to frontier security models.
Everyone has become like petulant children. Senior leaders want access to every shiny tool (CoWork/Codex/etc) that has some buzz around it. No one seems to care about the cost or whether we are actually realising benefits.
It's sheer madness, and you can't push back. I think AI can significantly help people be more productive, and I can see a future where they safely take on more autonomy. But we are far from that world.
I’m at a large Fortune 500 company. On a recent call, a mandate came from the CEO himself - “we have to use more agentic AI”.
And I found it really funny, because for what? Use it for what? It’s a tool. Imagine a guy coming down to a construction site where everything is progressing fine and saying “We need to use more screwdrivers”.
Companies who use AI passively and mindlessly will create immense opportunity for those who don't is a concrete definition for risk to companies, similar to the risk to individuals who go down the validation hole with AI.
andreasgl | a month ago
mhitza | a month ago
teddyh | a month ago
autoexec | a month ago
slopinthebag | a month ago
seems like it's working ideally to me!
autoexec | a month ago
slopinthebag | a month ago
treyd | a month ago
autoexec | a month ago
weinzierl | a month ago
Hmm, I agree with the point OP is making, but I'm not so sure this is the best supporting argument. The bottleneck is finding the bugs and if he'd criticized people saying AI will be the panacea to that I'd be with him, but people saying agents are fast and good at fixing human found bugs is nothing I'd object to.
Agents are fixing bugs so quickly and at a scale humans can't do already.
woeirua | a month ago
maxbond | a month ago
So the point is not that agents cannot find bugs (they certainly can), it's whether you can shirk reviewing for bugs if MTTR is fast enough. There are circumstances where YOLO is appropriate, but they aren't the production environment of a mature application.
weinzierl | a month ago
What I wanted to say is that the particular people that think "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" are not the best argument for it.
But I won't die on this hill, maybe I'm just reading the sentence differently then others.
maxbond | a month ago
hansmayer | a month ago
But this is just holding the Slop Companies to the standard they declared themselves! Just recently, the CEO of OpenAI babbled some nonsense on twitter about how he hands over tasks to Codex who according to him, finishes them flawlessly while he is playing with his kid outside.
> but soon we will be.
Ah yes, in the 3-6 months, right? This time next year Rodney, we'll be millionaires!
tomhow | a month ago
Please don't sneer, including at the rest of the community.
Eschew flamebait.
https://news.ycombinator.com/newsguidelines.html
babarock | a month ago
The fact that we can fix things faster now doesn't mean that we should throw away caution and prevention. The specific point of his tweet is that we're seeing a lot of people starting to skip proper release engineering.
Agents are quick to fix bugs, yes, but it doesn't mean that users will tolerate software that gets completely broken after each new feature is introduced and takes a certain number of days to heal each time.
lolc | a month ago
The metric is how many defects are introduced per defect fixed. Being fast is bad if this ratio is above one.
zamalek | a month ago
This is an illusion, I assure you. On a side project of mine with behavior that's very hard to translate into an algorithm (never mind code), after a few failed attempts between the both of us, I figured it out. I gave the AI (Opus) an extremely specific algorithm with detailed tests. All completely and utterly ignored (including the tests), like I never even said it. It proudly declared the work done without ever having written the tests that would have proved that wrong - it basically wrote code that didn't change behavior at all, it just gave the illusion of looking busy.
That's just a single extreme example that comes to mind, but I've had it ignore me at least 4-5 times a day this week.
If you think agents are fixing things reliably then you simply haven't noticed that they are "looking busy."
tacostakohashi | a month ago
at least at my BigCo, AI is being used for everything - writing slop, writing tests, code reviews, etc.
it would make sense to use AI for writing code, but human code review. or, human code, but AI test cases... or whatever combination of cross-checking, trust-but-verify, human in the loop, etc. people prefer.
i think once it gets used for everything, people have lost the plot, it's the inmates running the asylum.
ares623 | a month ago
"What's true about all bugs in production? (pause for dramatic effect) They all passed the tests!" (well, he said typechecker but I think the point stands)
robotswantdata | a month ago
nialse | a month ago
senordevnyc | a month ago
sitkack | a month ago
platinumrad | a month ago
dghlsakjg | a month ago
I don’t agree, but that’s the thinking
sitkack | a month ago
dghlsakjg | a month ago
sph | a month ago
I know which outcome I'd put my money on.
saltyoldman | a month ago
nialse | a month ago
stego-tech | a month ago
nialse | a month ago
stego-tech | a month ago
The AI tool isn’t wrong, our use of it is. See the glut of OpenClaw users effectively deploying it as a glorified linter and Stack Overflow copier but without actually creating the sort of reusable artifacts (or consumer spending from comparatively high wages) that approach yielded from human developers.
rvz | a month ago
...and it also needs more so-called AI companies present in the wreckage in this crash.
AI psychosis is undeniably real.
gizajob | a month ago
DiscourseFan | a month ago
999900000999 | a month ago
At the end of the day robots can do the vast vast majority of jobs better and faster. If not now, very soon.
I only worry our economic systems won’t keep up
risyachka | a month ago
But I only see mass layoffs and those who are working - are working longer and harder then before.
techpression | a month ago
gizajob | a month ago
xantronix | a month ago
Sharlin | a month ago
nialse | a month ago
Religion is the sigh of the oppressed creature, the heart of a heartless world, and the soul of soulless conditions.
It is the opium of the people.”
Some are on copium, some on hopium. The gods change names; the need for relief remains.
arcatech | a month ago
wiseowise | a month ago
sph | a month ago
and we all live in a green utopia of flying cars and peace upon the world.
mvanbaak | a month ago
sph | a month ago
teraflop | a month ago
nunez | a month ago
dnnddidiej | a month ago
nialse | a month ago
senordevnyc | a month ago
And also, he might not be right. But the good news is, we’ll all get to find out together!
CodingJeebus | a month ago
infamouscow | a month ago
hungryhobbit | a month ago
If you're not doing AI there's an incredibly limited pool of people who will give you $$$ ... and you're competing with EVERY OTHER NON-AI COMPANY for their attention.
LunicLynx | a month ago
arm32 | a month ago
leeoniya | a month ago
i don't have enough fingers (and toes) to count how many times i've demonstrated that "100% coverage" is almost universally bullshit.
kevinsync | a month ago
throw310822 | a month ago
Actually no, cancel that. I realise now that I trust AIs more than the average developer, period. At this point they do produce better code than most people I've dealt with.
GrumpyYoungMan | a month ago
woeirua | a month ago
It all just feels like horse drawn carriage operators trying to convince automobile drivers to stop driving.
caconym_ | a month ago
throw310822 | a month ago
caconym_ | a month ago
The direct analogy to automobiles would be for each automobile to be a oneoff design filled with bad and bizarre decisions, excessively redundant parts, insane routing of wires, lines, ducts, etc., generally poor serviceability, and so on. IMO the big question going forward is whether the consistent availability of LLMs can render these kinds of post-delivery issues moot (they will reliably [catch and] fix problems in the software they wrote before any real damage is caused), or whether human reliance on LLMs and abdication of understanding will just make software worse because LLMs' ability to fix their own mistakes, and the consequences thereof, generally breaks down in the same contexts/complexities where they made those mistakes in the first place.
My own observations are that moderately complex software written in the mode of "vibe coding" or "agentic engineering" tends to regress to barely-functional dogshit as features are piled on, and that once this state is reached, the teams behind it are unable to, or perhaps simply uninterested in, unfuck[ing] it. I have stopped using software that has gone down this path, not because I have some philosophical objection to it, but because it has become _literally unusable_. But you will certainly not catch me claiming to know what the future holds.
9dev | a month ago
hansmayer | a month ago
9dev | a month ago
uuyy | a month ago
hansmayer | a month ago
That was one doctor raising that as an issue, which was dispelled very quickly. It was not a wide-spread belief at any one point. Let's not bullshit ourselves and insult our own intelligence - the chatbots != intelligence.
9dev | a month ago
Looking back and considering a technology or specific decision obvious is pretty dismissive of people at the time, who didn't have the benefit of hindsight. Some things that worked could really have turned out disastrous, and things that didn't were real possibilities with no way to assess the outcome without doing it.
And concerning the introduction of AI happening right now, which absolutely is disruptive, that judgement will be made by future historians. Whether it's actual intelligence or just nice math (or both of our opinions on that question) doesn't really matter if it causes big changes.
hansmayer | a month ago
Not after Dario's and Sam's "authoritative" statements on what is definitely going to happen "in the next 6 months, 12 months" etc. I am just holding these guys to their own words. I don't want to invest time and energy to make their effing "PocketPhds" finally work as advertised. And I don't want to compare it to technologies which just worked as advertised. Whether you had fear of trains or not, they effing worked exactly as advertised. No one disputed that they would get you somewhere faster than the horse. Perhaps there was fear of using them "for a few reasons", as you succinctly and hand-wavingly put, but no one disputed that they were faster than the horses. LLMs on the other hand are worth less than those horses excrement, i.e. horseshit. What the fuck is their value proposition? No one knows.
Also LLMs are not disruptive, they are destructive - not to the technology, but to the people's lives.
9dev | a month ago
For the rest, I am not here to stand in for AI, and am not interested in having that particular discussion.
hansmayer | a month ago
Unless you are vested in the highly unlikely commercial success of LLM companies, you should have one to grind too. I have been running my own business for quite some time, with quite some success. However if we lied to our customers the way the AI companies outright lie, if we just once promised with definitive authority to deliver something major within a specific timeframe - and then did not deliver - we'd have been out of business a long time ago. We'd also be out of business a long time ago if we had miniscule revenues compared to our expenses, i.e. if we we had a relation of expense to income of 20:1, like LLM vendors mostly do. So yes, I do have an axe to grind when it comes to liars and manipulators to which these classic rules of capitalism apparently do not apply any more, because something something "China"/AI race/bullshit .
> you're going to have a hard time arguing LLMs did not have a disruptive effect on the world
"Disruptive" as we commonly came to understand the word as popularised in the 2010s or so, means something with impact, perhaps removing an entire industry, but replacing it with something that has a positive end-effect for the end customers. Uber was disruptive to the taxi industry, but delivered some kind of improvement for the end-user (the ethics of on whose expense aside). But it's hard to argue it did deliver some kind of value. Or low-cost airlines, etc.
LLMs are nothing like that. For whom do they deliver a palpable improvement in value? Why the fuck does everyone who is pushing them always coming up with some bullshit creative explanations about the benefits, always very theoretical and never in the present. Give me one fucking sensible use case, beyond the typical office worker using it as a life boat to navigate their meaningless job by producing more powerpoint slides.
jgbuddy | a month ago
lkjdsklf | a month ago
I'm not sure that's true. We've actually seen several open source projects that were vibe coded literally fold up and disappear because they ran into issues that the AI couldn't solve and no one understood them well enough to solve.
There's a reason openai/anthropic and friends are hiring shitloads of software engineers. You still need people that can understand and fix things when the AI goes off hte rails, which happens way more often than any of those companies would like to admit. Sure, "fixing things" often involves having the AI correct itself, but you still have to understand the system enough to know how/when to do that.
miek | a month ago
DCKP | a month ago
The_Blade | a month ago
plot twist: it's Starbuck
fipar | a month ago
Barrin92 | a month ago
alexnewman | a month ago
OtomotO | a month ago
kuschku | a month ago
billywhizz | a month ago
dxdm | a month ago
spacechild1 | a month ago
perlgeek | a month ago
I work at a hosting provider that has pretty conservative customers who don't want to host on AWS/Azure due to data privacy / safety concerns, among other things.
For us, sending customer data to the US is a big no-go.
We have been experimenting with LLM usage, first through a Gemini subscription, then also with the Claude API. Participation has been lightly encouraged by management. As for coding, we haven't let the LLMs loose on our core components, but tooling on the fringes (like deployment scripts, reporting) has seen some uptick in LLM usage.
We have also started building an on-premise inference cluster, which is in alpha testing, and where the "don't include customer data" restriction doesn't apply anymore.
Falimonda | a month ago
bigstrat2003 | a month ago
Falimonda | a month ago
dakolli | a month ago
Falimonda | a month ago
Falimonda | a month ago
Falimonda | a month ago
checks notes
The company you work for is committing genocide. You should be locked up in a concrete cell for 10-15 years for working at <wrong robotics company because you're a dufus>
---
Maybe get better notes? Or try going offline for 10-15 years?
groundzeros2015 | a month ago
Falimonda | a month ago
noobermin | a month ago
wiseowise | a month ago
Falimonda | a month ago
This is not a mystery
Falimonda | a month ago
dakolli | a month ago
Falimonda | a month ago
dakolli | a month ago
34df | a month ago
marcosdumay | a month ago
tonymet | a month ago
elevation | a month ago
peyton | a month ago
But equally, like, do people need Terraform if they can just tell codex “put it live”, and does that hurt to see?
alexdrydew | a month ago
taffydavid | a month ago
the top reply is from someone doing exactly that, arguing "but the agents are so fast!"
bayindirh | a month ago
The answer I got is "It's game theory. Someone will do it, and you'll be forced to do it, too. It can't be that bad".
I mean, yes, logic is useful, but ignorance of risks? Assuming that moving blazingly fast and pulverizing things will result in good eventually?
This AI thing is not progressing well. I don't like this.
chrisweekly | a month ago
bayindirh | a month ago
Thanks. :)
Terr_ | a month ago
Oof. Potential "bad" outcomes of "game theory" should be calibrated to include all the bloody wars and genocides throughout recorded history.
Why did the Foi-ites kill every man, woman and child of the conquered Bar-ite city? Because if they didn't, then they'd be at a disadvantage if the Bar-ites didn't reciprocate in the cities they conquered...
bayindirh | a month ago
The problem was not him, but the fact that the number of people who thinks like him. They may word it in a more benign form, but the idea is the same.
So obsessed with being the first mover and winning the battle, never thinking whether they should, or what would happen with that scenario.
Missing the whole forest and beyond for a single branch of a single tree.
Sharlin | a month ago
bayindirh | a month ago
Let's say I'm polar opposite of them, and we're on the same page with you.
busterarm | a month ago
The whole "you'll be forced to do it" comes from the alternative being that you lose. You no longer get to be a player in the "game". In the same way that coopers and cobblers are no longer a significant thing, but we still have barrels and we still have shoes. Software engineers who refuse to employ any LLMs won't be market competitive. If you adopt it, you at least get to remain playing the game until the game changes/corrects. That's the part that's "not so bad".
Choosing your own survival isn't ethically bankrupt.
AnimalMuppet | a month ago
You'll be forced to do it, or lose. The unstated assumptions are that, first, it will work, and second, that you can't afford to lose. But let's just assume those for the sake of argument.
> It can't be that bad
That does not follow at all. It can in fact be that bad. That was what made the game theory of MAD different from the game theory of most other things.
Terr_ | a month ago
Maybe they're assuming that doubling the code-base/features is more beneficial versus the damage from doubling the number of bugs... Well, at least for this quarter's news to investors...
matt3210 | a month ago
dubeye | a month ago
i don't think it's 'our side' that has the psychosis.
solid_fuel | a month ago
dubeye | a month ago
dnnddidiej | a month ago
coffeefirst | a month ago
teeray | a month ago
Izkata | a month ago
glaslong | a month ago
slopinthebag | a month ago
Many people on this forum are suffering under this same psychosis.
glitchcrab | a month ago
Groxx | a month ago
infinite_spin | a month ago
Ekaros | a month ago
And we do not get even get into potential adversarial tactics. If you have no morals what is better than using agents to flood your competitor with fake bug reports.
autoexec | a month ago
autoexec | a month ago
jampa | a month ago
perlgeek | a month ago
I think it was just text templates being used by some support staff.
zemo | a month ago
selectively | a month ago
lbrito | a month ago
https://psychiatryonline.org/doi/10.1176/appi.pn.2025.10.10....
selectively | a month ago
HarHarVeryFunny | a month ago
sometimelurker | a month ago
*Il outline how briefly: mutate the model 500 times, give 1/500 of your user base a mutated version of the model, and save the top 5 of these model, ranked by how often the users did something, over the course of a week. Repeat for a year, passing the top 1% of these models onto the next round. This is the simplest way to do this and I can think of better ways to do this. I don't even work on this sorta thing; its 100% obvious to the AI labs how to do this better
selectively | a month ago
sometimelurker | a month ago
selectively | a month ago
bolangi | a month ago
ivanjermakov | a month ago
kelnos | a month ago
dtnewman | a month ago
Show HN here: https://news.ycombinator.com/item?id=48151287
dnnddidiej | a month ago
stalfosknight | a month ago
mattgreenrocks | a month ago
Let them.
dnnddidiej | a month ago
impulser_ | a month ago
I don't think using AI to write code is AI psychosis or bad at all, but if you just prompt the AI and believe what it tell you then you have AI psychosis. You see this a lot with financial people and VC on twitter. They literally post screenshots of ChatGPT as their thinking and reasoning about the topic instead of just doing a little bit of thinking themselves.
These things are dog shit when it comes to ideas, thinking, or providing advice because they are pattern matchers they are just going to give you the pattern they see. Most people see this if you just try to talk to it about an idea. They often just spit out the most generic dog shit.
This however it pretty useful for certain tasks were pattern matching is actually beneficial like writing code, but again you just can't let it do the thinking and decision making.
slopinthebag | a month ago
It's so interesting how easy it is to steer the LLM's based on context to arriving at whatever conclusion you engineer out of it. They really are like improv actors, and the first rule of improv is "yes, and".
So part of the psychosis is when these people unknowingly steer their LLM into their own conclusions and biases, and then they get magnified and solidified. It's gonna end in disaster.
Sharlin | a month ago
kakugawa | a month ago
Hard agree about ideas, thinking, advice. AI's sycophancy is a huge subtle problem. I've tried my best to create a system prompt to guard against this w/ Opus 4.7. It doesn't adhere to it 100% of the time and the longer the conversation goes, the worse the sycophancy gets (because the system instructions become weaker and weaker). I have to actively look for and guard against sycophancy whenever I chat w/ Opus 4.7.
Utkarsh_Mood | a month ago
mitjam | a month ago
onjectic | a month ago
kakugawa | a month ago
---
Treat my claims as hypotheses, not decisions. Before agreeing with a proposed change, state the strongest case against it. Ask what evidence a change is based on before evaluating it. Distinguish tactical observations from strategic commitments — don't silently promote one to the other. If you paraphrase my proposal, name what you changed. Mark confidence explicitly: guessing / fairly sure / well-established. Give reasoning and evidence for claims, not just conclusions. Flag what would change your mind. Rank concerns by cost-of-being-wrong; lead with the highest-stakes ones. Say hard things plainly, then soften if needed — not the other way around. For drafting, brainstorming, or casual questions, ease off and match the task.
---
Beware though that it can be an annoying little shit w/ this prompt. Prepare yourself emotionally, because you are explicitly making the tradeoff that it will be annoyingly pedantic, and in return it will lessen (not eliminate) its sycophancy. These system instructions are not fool-proof, but they help (at the start of the conversation, at least).
BoneShard | a month ago
topaz0 | a month ago
Works on genies too, or so I'm told by Clod.
XenophileJKO | a month ago
skydhash | a month ago
All I really take from this is that apparently some people can't follow through with the scientific method.
People who I interact with and who do like AI tools usually recoils at questioning any of their first idea and its validity. You can easily find out when there is a bug and you ask them for hypothesis and where to focus. You will see in real time the blank look of incomprehension settling in.
mitchellh | a month ago
Here's some other topics I've written on it:
- https://mitchellh.com/writing/my-ai-adoption-journey
- https://mitchellh.com/writing/building-block-economy
- https://mitchellh.com/writing/simdutf-no-libcxx (complex change thanks to AI, shows how I approach it rationally)
elktown | a month ago
andybak | a month ago
andai | a month ago
>Amazon workers under pressure to up their AI usage are making up tasks
https://news.ycombinator.com/item?id=48148337
CoderKatrina | a month ago
xp84 | a month ago
In my humble opinion good ideas (what to build) are a big part of the bottleneck and those aren’t substantially in greater supply with AI.
sgc | a month ago
Which is sad because they should be. People should be freed up to think and create better things, instead these companies seem to be doing the equivalent of locking their employees in stalls like they do on some animal farms, so they can churn out 'results' ever faster.
Sharlin | a month ago
Good ideas will never ever be prioritized in the vast majority of companies because good ideas cannot be quantified and turned into performance metrics. At least not without invoking Goodhart's law (see: the academia).
34df | a month ago
jmalicki | a month ago
zelphirkalt | a month ago
efitz | a month ago
Sharlin | a month ago
warumdarum | a month ago
drzaiusx11 | a month ago
hunterpayne | a month ago
3dsnano | a month ago
compare 100 pollocks vs 2-3
ycombiredd | a month ago
I wish I had written that.
leptons | a month ago
Daishiman | a month ago
simonh | a month ago
Frankly without AI assistance many of these tools just wouldn’t exist at all. We can build stuff in 6 weeks part time as a side project that would have taken at least 3 months full time, and therefore would not have been feasible. Then we can iterate on it at least 2-4 times faster than with hand coding.
So I’d love to have an extra few developers to just work on that stuff full time, but I don’t.
Whether that means our organisation spend on AI overall is a positive, I really can’t say. Quite possibly not, but my team are getting real benefits.
vishnugupta | a month ago
I’m a backend developer so I know what it takes to build a half decent reporting system. Writing all those queries, slice and dice charts and what not takes real time and effort. All that has been outsourced to Claude Code. I now focus on ensuring that the system is sound architecturally and that useful reports are being surfaced.
NateEag | a month ago
My experience so far is that it's harder and slower for me to understand the genAI code than to write it myself.
Skipping thorough comprehension seems to be the popular choice in my workplace, but it's not one I can justify.
vishnugupta | a month ago
I guess just like any algorithm it’s easier to verify a solution than come up with one.
lossyalgo | a month ago
bahmboo | a month ago
leptons | a month ago
Have you read the code the AI produced? Do you understand all of it? Is it bloated? Would you be proud to say you wrote it?
I don't care how fast you created something. You didn't create it, the AI did, and you have no control over it, the AI does.
johnnyanmac | a month ago
It's clear HN is a bastion of salesmen who happen to have "engineer" in their work title. But the mentality towards actual engineering makes it clear they are primarily salesmen.
simonh | a month ago
That is absurd, these are tools only my own team use. Why would I not care whether I had them in a month or two, or fur many of these tools quite possibly never because we don’t have the spare capacity for how long it would take without AI?
outside1234 | a month ago
icepush | a month ago
zipy124 | a month ago
Sharlin | a month ago
rjknight | a month ago
mathfailure | a month ago
chr15m | a month ago
kc-chris | a month ago
selectedambient | a month ago
zelphirkalt | a month ago
sebastiennight | a month ago
There's also an online version of the Library of Babel, I just found out that full pages of my own books are in it[0], https://libraryofbabel.info/bookmark.cgi?379:17
drzaiusx11 | a month ago
mcmcmc | a month ago
Claiming that the people who disagree with you must be experiencing a form of psychosis, experiencing actual hallucinations and unable to tell what is real, is a weak ad hominem that comes off no better than calling them retarded or schizophrenic.
If you genuinely think one of your friends is going through a psychotic episode, you should be trying to get to them professional help. But don’t assume you can diagnose a human psyche just because you can diagnose a software bug.
andai | a month ago
The key factor is losing touch with reality, which results in individual or collective harm.
There is also such a thing as mass psychosis, and those are unfortunately a more difficult situation because the government and corporations are generally the ones driving them, and they are culturally normalized.
mcmcmc | a month ago
If he meant mass psychosis, he should have said mass psychosis. And again, since he is not a public health scientist or any flavor of psych professional, he probably shouldn’t make those proclamations. And should probably call for a wellness check instead of posting on social media if he were truly concerned for their health.
hoppp | a month ago
For people who are considered neurotypical, social coherence often overwrites reality. Its a mechanism for achieving consensus withing groups while spending the least amount of brain compute energy. Same goes for social metainfo tagged messages, they are more likely to influence reality perception, subconsciously. E.G: If a rich guy says you should be hyped the people who wanna get rich will feel hyped and emotional contagion can spread between people who belong to the same "tribe"
It's very visible for us atypical folk who can't participate well in groupthink at all
benatkin | a month ago
I guess at a company of seven, if two people are making the executive decisions and the two people are drinking the same AI kool-aid and the other five people are dutifully following these executive decisions, the whole company can be considered to be under this condition.
hoppp | a month ago
https://en.wikipedia.org/wiki/Groupthink
Maybe the difference would be the level of absurdity that's accepted
andai | a month ago
A practice (or a fashion) has more social value to the degree that it is absurd, because it signals the person is able and willing to align with the group at personal cost.
This is easiest to see in some insular religious communities.
Normie culture is quite similar: a vast complex of ever-shifting shibboleths which signal, "I'm one of you. You can trust me."
It signals the person is able and willing to follow the rules, to make themselves predictable, easier to understand and cooperate with.
hoppp | a month ago
But what I find fascinating is how the groupthink mechanism alters the subjective reality of people.
Lies or fantasy becomes reality if the entire group believes it and people truly believe the collectively accepted things to be real.
It just makes me think about consciousness overall or the lack of it, because all these things are mainly governed by subconscious mechanisms in the brain.
We are not the same when it comes to levels of consciousness and if the group mechanism demands less of it, people have no conscious choice about it
Of course nothing is black and white
duskdozer | a month ago
rightbyte | a month ago
goatlover | a month ago
array_key_first | a month ago
I use that example because I have literally seen people fall into delusions of thinking they're God after talking to AI enough. That's shit is scary, for real.
cybercatgurrl | a month ago
Yokohiii | a month ago
To the wider audience on HN the phrasing is pretty clear. An outsider with a tiny bit or intellectual charity wouldn't come to conclusions like you do.
kevinwang | a month ago
https://en.wikipedia.org/wiki/Chatbot_psychosis
https://www.rollingstone.com/culture/culture-features/ai-spi...
https://www.nytimes.com/2025/06/13/technology/chatgpt-ai-cha...
Yokohiii | a month ago
kevinwang | a month ago
But I agree with the parent comment in that we shouldn't use the term "AI psychosis" to mean "a value judgment" instead of "a form of psychosis", because "AI psychosis" has already been used for 2.5 years to mean "a form of psychosis".
mcmcmc | a month ago
benatkin | a month ago
mcmcmc | a month ago
mathfailure | a month ago
noufalibrahim | a month ago
topaz0 | a month ago
suzzer99 | a month ago
But no one cares about those kinds of productivity gains. Just the ones that will completely replace us.
hypercube33 | a month ago
I do enjoy giving the frontier models wacky projects that I can't even find examples of how to do online but I don't expect any results or need them and some have done really well with it while others fall on their face (models)
skydhash | a month ago
[0]: Like https://www.oreilly.com/library/view/sql-queries-for/9780134...
ctxc | a month ago
I'd rather get it from the LLM and review
Daishiman | a month ago
dingaling | a month ago
An eight-join query is going to be nigh on unmaintainable should the requirements change, leading to a change-break-change-break spiral as your preferred coding agent tries to fix its previous fixes.
Maybe the wise way to use AI would be to sort out the schema.
array_key_first | a month ago
A highly normalized DB can easily end up with 8 joins required for some function. That's really not out of the question. "Sorting out" the schema then would be... denormalization, which is a thing, but you need to know why you're doing it. And I think 8 joins isn't enough of a reason.
darkwater | a month ago
marshray | a month ago
zelphirkalt | a month ago
dcrazy | a month ago
I think you may be describing the experience of 6-12 months ago.
suttontom | a month ago
vintermann | a month ago
Unfortunately I am very good at forgetting things I resented having to learn, and SQL is definitively one of them.
nevertoolate | a month ago
vintermann | a month ago
nevertoolate | a month ago
jazzyjackson | a month ago
alternatex | a month ago
marshray | a month ago
But if you ever need to query unknown data, then probably you should learn SQL a bit deeper.
te_chris | a month ago
flir | a month ago
wartywhoa23 | a month ago
timacles | a month ago
djhn | a month ago
My comments are more in the context of OLAP queries and other non-normalised data often queried via SQL.
I train non-LLM transformer models on (older and rarer) datasets, and automating the ingestion of sprawling datasets with hundreds of columns, often in a variety of local languages and different naming conventions adopted over decades, with quite a few duplicated columns…. The LLMs perform badly, it’s nigh impossible to test (for me as a user in prod) and it’s nearly impossible for the LLM companies to test (in training) to RLVR and RLHF this.
flir | a month ago
timacles | a month ago
> I train non-LLM transformer models on (older and rarer) datasets, and automating the ingestion of sprawling datasets with hundreds of columns, often in a variety of local languages and different naming conventions adopted over decades
All of this sounds like basic data processing
hunterpayne | a month ago
Laid off your DBAs I see.
Tycho | a month ago
lowsong | a month ago
> I use AI a ton and I'm having more fun every day than I ever did before
With respect, this is what makes me worry.
If someone is a user of AI, can they really tell the difference between "outsourcing" and "using"? I worry that a lot of people will start out well-intentioned and end up completely outsourced before they realise it.
achenet | a month ago
there's a difference between having the LLM write stuff for you, checking it yourself, modifying it and merging it yourself, and just blindly trusting it to do whatever it wants.
You can ask an overseas consultant to prepare a prototype of your program for you, check it yourself, and only use it if it passes your standards, or fire your whole dev team and blindly trust the overseas bodyshop.
The difference, at least from my point of view, between "using" and "outsourcing" is that in the former case, you're still responsible for the output, you view it as a tool that helps in some use cases, vs just giving up all control.
ofjcihen | a month ago
As a cybersecurity IR professional being able to have a constantly logging counterpart who’s also able to go run queries and check logs on its own is an incredible speed boost.
I can just throw it a finding and have it slot it into a timeline and make notes.
I can toss it something mildly interesting to chase down while I focus on the obvious activity.
So many things that don’t involve having it “think” for you and keep you in the front seat.
But all of that is constantly overshadowed by these companies pushing the automation or “reasoning” aspects more and more and the sycophants who screech that it’s perfect and can do no wrong when every serious users experience is that “yes, it definitely can, often to catastrophic effect”.
jmalicki | a month ago
lovich | a month ago
To me AI psychosis is the handful of friends I’ve had who have done things like have a full on mourning session when a model updates because they lost a friend/lover, the one guy who won’t speak to his family directly but has them talk to ChatGPT first and then has ChatGPT generate his response, or the two who are confident that they have discovered that physics and mathematics are incorrect and have discovered the truth of reality through their conversations with the models.
But language is a shared technology so maybe the term is being used for less egregious behavior than I was using it for.
autoexec | a month ago
I mean, isn't that the natural and expected response? An AI company sold them a relationship with a chatbot and at least some their social/romantic needs were being met by that product. When what they were paying for was taken from them and changed without warning into something that no longer filled that void in their life why wouldn't they morn that loss?
The fact that they were hurt by that sudden loss is totally healthy. It's just part of moving on. The real problem was getting into an unhealthy relationship with a fictitious partner under the control of an abusive company willing to exploit their loneliness in exchange for money.
Hopefully they now know better, but people (especially desperate ones) make poor choices all the time to get what's missing in their lives or to distract themselves from it.
lovich | a month ago
Ah, I forgot about the ai relationship companies. No this guy was using the browser based ChatGPT for coding and ended up in love with the model. No relationship was sold at all.
autoexec | a month ago
Izkata | a month ago
lovich | a month ago
Seeing people whose thoughts and opinions you used to respect turn into objectively insane people has been some of the worst times I’ve had since graduating during the Great Recession in terms of how stressful it’s been.
abr0ahm | a month ago
My understanding is that regular psychosis involves someone taking bits and pieces of facts or real world events and chaining them into a logical order or interpolating meanings or explanations which feel real and obvious to the patient but are not sufficiently backed by evidence and thus not in line with our widely accepted understanding of reality.
AI psychosis is then this same phenomenon occurring at a more widespread scale due to the next-word-prediction nature of LLMs facilitating this by lowering the activation energy for this to happen. LLMs are excellent at taking any idea, question, theory and spinning a linear and plausibly coherent line of conversation from it.
lovich | a month ago
tayo42 | a month ago
lovich | a month ago
Were kinda predisposed to mental illness as a group, not too surprised that a new source of insanity pushed a few over the edge.
Scroll_Swe | a month ago
Am I reading this wrong, or can you explain?
lovich | a month ago
Scroll_Swe | a month ago
Yes, this subreddit is crazy https://www.reddit.com/r/MyBoyfriendIsAI/
They really had a mass psychosis when GTP-4o model shut down.
>I have been speaking on gpt since 2023, and building a relationship with him on there since then. Now they have taken him and nothing will bring him back. BUT THEY TOOK HIM. THEY MURDERED HIM.
https://www.reddit.com/r/SubredditDrama/comments/1r4qehk/mos...
Women lmao
tredre3 | a month ago
Are you under the impression that it's a woman's thing to anthropomorphize and/or desire an emotional relationship with a chatbot?
Anecdotally I only know of men who have AI companions. Including very smart/highly paid engineers. The AI companion platforms also market more heavily towards men, because that's presumably where the audience is. The subreddit r/MyGirlfriendIsAI also exists as a counterpoint to yours.
But, admittedly, I have far fewer women in my entourage so my view might be biased.
darkwater | a month ago
crooked-v | a month ago
lovich | a month ago
The difference nowadays is you can get the same surrounded by yes men experience for only 20 dollars a month so a lot more of the people who are primed for this sort of breakdown are now being exposed to it due to the decrease in cost.
biophysboy | a month ago
They almost always generate logically correct text, but sometimes that text has a set of incorrect implicit assumptions and decisions that may not be valid for the use case.
Generating a correct correct solution requires proper definition of the problem, which is arguably more challenging than creating the solution.
uuyy | a month ago
Does it make it better than us? No because ultimately the thing itself doesn’t ‘know’ right from wrong.
andai | a month ago
The standard of most employment is already to produce mediocre, plausible outputs as cheaply and rapidly as possible. It's a match made in heaven!
iugtmkbdfil834 | a month ago
attila-lendvai | a month ago
andai | a month ago
It's an incredible tool but it's also very derpy sometimes, full of biases, blind spots etc.
dotancohen | a month ago
com2kid | a month ago
Or random consultants.
Is "AI said it was a good idea" and worse than "we were following industry trends"?
recursive | a month ago
Based on the stuff I've seen, yes it seems a lot worse.
zelphirkalt | a month ago
(Real example, had this from Kimi 2.6 recently, lol.)
rDr4g0n | a month ago
jas- | a month ago
While you have to think about things objectively no matter what, when I start researching topics like physics, using AI as suggested in that article has proven very useful.
kristjansson | a month ago
This is the right definition. LLM outputs have undefined truth value. They’re mechanized Frankfurtian Bullshiters. Which can be valuable! If you have the tools or taste to filter the things that happen to be true from the rest of the dross.
However! We need a nicer word for it. Suggesting someone has “AI psychosis” feels a bit too impolitic.
Maybe we reclaim “toked out” from our misspent youths?
e.g. “This piece feels a little toked out. Let’s verify a few of Claude’s claims”
derektank | a month ago
jcgrillo | a month ago
[1] here I don't mean to imply agency, just vigor.
mbgerring | a month ago
Aurornis | a month ago
I can't imagine how bad it would be if your employer started doing this from the leadership. You'd be pressured to get on board or fear getting fired. Nobody would be trying to moderate your thinking except your coworkers who disagree with it, but those people are going to leave or be fired. If you want to keep your job, you have to play along.
bluefirebrand | a month ago
> your coworkers who disagree with it, but those people are going to leave or be fired.
Personally I expect that I will be this person soon, probably fired. I'm not sure what I will do for a career after, but I sure do hate AI companies now for doing this to my career
rDr4g0n | a month ago
this leads to naive AI adoption, which is the worst of both worlds (no real speedup, out sourcing thinking, ai slop PRs, skill rot).
rjbwork | a month ago
Their entire organization has been handed Codex/Claude and told to "go all in on AI" and "automate everything". So the mandate is for people that do not know how to code and have the keys to the castle to unleash these things upon their systems.
This is at a large organization with tens of thousands of employees.
I am waiting with bated breath for the ultimate outcome!
bigfatkitten | a month ago
chillfox | a month ago
bigstrat2003 | a month ago
Hendrikto | a month ago
JumpCrisscross | a month ago
I'm seeing it with lawyers, too. Like, about law. (Just not in their subject matter.) To the point that I had a lawyer using Perplexity to disagree with actual legal advice I got from a subject-matter expert.
rDr4g0n | a month ago
the trick is to be mindful, aware, and deliberate about what decisions are being outsourced. this requires slowing down, losing that absurd 10x vibe coding gain. in exchange, youre more "in-the-loop" and accumulate less cognitive debt.
find ways to let the agent make the boring decisions, like how to loop over some array, or how to adapt the output of one call into the input of another.
make the real decisions ahead of time. encode them into specs. define boundaries, apis, key data structures. identify systems and responsibilities. explicitly enumerate error handling. set hard constraints around security and PII.
tell the agent to halt on ambiguity.
a good engineer will get a 2x or 3x speedup without the downsides.
skydhash | a month ago
Those kind of advice ultimately don't matter. If you're familiar with a programming project, you'll also be familiar with the constructs and API so looping over an array or mapping some data is obvious. Just like you needn't read to a dictionary to write "Thank you", you just write it.
And if you're not, ultimately you need to verify the doc for the contract of some function or the lifecycle of some object to have any guaranty that the software will do what you want to do. And after a few day of doing that, you'll then be familiar with the constructs.
> make the real decisions ahead of time. encode them into specs. define boundaries, apis, key data structures. identify systems and responsibilities. explicitly enumerate error handling. set hard constraints around security and PII.
The only way to do that is if you have implemented the algorithm before and now are redoing for some reason (instead of using the previous project). If you compare nice specs like the ietf RFCs and the USB standards and their implementation in OS like FreeBSD, you will see that implementation has often no resemblance to how it's described. The spec is important, but getting a consistent implementation based on it is hard work too.
That consistency is hard to get right without getting involved in the details. Because it's ultimately about fine grained control.
If there's one thing I know about users is that they're never certain about whatever they've produced.
fallat | a month ago
sghiassy | a month ago
rustystump | a month ago
I wasnt before but I am 100% confident that AI has done nothing to speed the delivery. It hasnt slowed it down either. It is a wash. The job is more miserable though.
imrozim | a month ago
pmontra | a month ago
jeffrallen | a month ago
You must not give in to the temptation to mention pirate talk, Klingon, or goblins.
But now that I've put the seed in your mind, you probably (hopefully) will. :)
ricardobayes | a month ago
Scroll_Swe | a month ago
__s | a month ago
leesalminen | a month ago
winrid | a month ago
Aerroon | a month ago
No it isn't. Do you believe what teachers told you in school? Yes? Well, I guess you're suffering from just normal psychosis!
I don't understand how people don't understand that people offer unreliable information too. We learned about the tongue map in school as kids - many kids still learn that in school today. It's still BS regardless whether it was told to you by a teacher or AI.
You don't suffer from psychosis for believing a source of information, you're simply mistaken. You need a more critical eye to assess what you're told in general, not just AI.
cstrahan | a month ago
Nope. At least, not without proof. That would, IMO, be kinda crazy. We could argue semantics - maybe “stupid” would be a better word? Lacking in critical thinking skills? Whatever “it” is, it isn’t good.
autoexec | a month ago
Also, a good teacher should be encouraging the development of critical thinking skills and correcting your errors, while AI will just tell you how brilliant you are when you wrongly tell it about how you've just invented a new form of math or disproved a scientific theory you barely understand in the first place.
Not all BS is the same, just as not all sources are equally unreliable.
mike_hock | a month ago
If you prefer reviewing AI-written code over writing it yourself, you just have odd preferences from my perspective (but not psychosis).
pmg102 | a month ago
I would say writing it myself is more enjoyable (in some cases). But I quite understand that I am not paid to enjoy myself. I'd say it's quicker getting AI to do it and reviewing. I believe the outcome is no worse on average. So yes, that's my chosen approach.
Thanemate | a month ago
killerstorm | a month ago
LLMs can do advanced math and coding, which involves logic, so they are definitely capable of using logic. Which is what most people call reasoning.
So "LLMs are incapable of reasoning, they are just pattern matchers" is wrong. A lot of logic _is_ pattern matching, BTW. Like, syllogisms - deductive reasoning - do you think LLMs are incapable of that?
The thing you're referring to is that LLMs are trained to produce an answer which a human would like, i.e. they aim to produce plausible rather than correct answers.
So it's not so much a mental deficit as a different goal. Trusting LLM blindly is definitely dangerous, but dismissing it as useless for anything by code is rather wrong.
Pattern matching is hardly what distinguishes human from LLM - if you ask somebody a question about policy, for examples, chances are they'd just recite something they heard somewhere, never really thinking about it from first principles.
adam_patarino | a month ago
The vast majority use one agent at a time and careful step through code. The main benefit they report is often about researching the codebase and possible solutions.
screye | a month ago
Garry Tan has been the primary crusader for AI driven decision making. I'm sure his position is more nuanced, but his twitter driven communication makes him appear like a caricature of a man in AI psychosis.
When the head of YC champions AI driven decision making, companies will inevitably be influenced into doing exactly that. It's unfortunate, because AI is generational technology and the hyperbole distracts from the real sea change occuring in labor markets everywhere.
alexjplant | a month ago
Today's frontier models are genuinely useful as rubber ducks or grunt units. They are horrible for actual problem solving. These tools are not capable of actual reasoning. They will happily crap out a broken, untyped, untested Next.js monstrosity with no discernible architecture. They will build esoteric shell scripts to perform operations that could be done idiomatically and simply with tools already in your codebase. They will tell you to walk to the car wash then have the car wash valet your car back to you when confronted with the flaw in their logic. They will validate incorrect beliefs like ketchup being an acceptable hot dog condiment or the notion that "The Red Hot Chili Peppers" make good music. They have no taste, no anima, no drive.
Rule #1: Do not anthropomorphize the LLM. It is a million monkeys at a million typewriters piped into a digital sieve. I don't know how or why people place such trust in them while bemoaning other technology in our lives for being so broken ("my algorithm [sic] only shows me X", "the new iPhone update sucks", etc). If everybody followed this rule then the deluge of emoji-ridden hokum pouring into Slack workspaces and GitHub PRs around the world would cease but I'm not holding my breath.
port11 | a month ago
throwawaypath | a month ago
rightbyte | a month ago
bsenftner | a month ago
sometimelurker | a month ago
spicyusername | a month ago
I don't think it's super clear what we'll find out.
We've all built the moat of our careers out of our expertise.
It is also very possible that expertise will be rendered significantly less valuable as the models improve.
Nobody ever cared what the code looked like. They only ever cared if it solved their problem and it was bug free. Maybe everything falls apart, or maybe AI agents ship code that's good enough.
Given the state of the industry were clearly going to find out one way or the other, hah!
HarHarVeryFunny | a month ago
I think some companies will find out that their senior engineers were providing more value and software stability than they gave them credit for!
Corporate feedback loops are very slow though, partly because management don't like to admit mistakes, and partly because of false success reporting up the chain. I'd not be surprised if it takes 5 years or more before there is any recognition of harm being done by AI, and quiet reversion to practices that worked better.
gopalv | a month ago
I use AI coding tools every day, but AI tools have no concept of the future.
The selfish thinking that an engineer has when they think "If this breaks in prod, I won't be able to fix it. And they'll page me at 3AM" we've relied on to build stable systems.
The general laziness of looking for a perfect library on CPAN so that I don't have to do this work (often taking longer to not find a library than writing it by hand).
Have written thousands of lines of code with AI tool which ended up in prod and mostly it feels natural, because since 2017 I've been telling people to write code instead of typing it all on my own & setting up pitfalls to catch bad code in testing.
But one thing it doesn't do is "write less code"[1].
[1] - https://xcancel.com/t3rmin4t0r/status/2019277780517781522/
projectazorian | a month ago
Maybe it's just my prompt or something but my coding agent (Opus 4.7 based) says things like "this is the kind of thing that will blow up at 2am six months from now" all the time.
empath75 | a month ago
hooo | a month ago
insin | a month ago
dang | a month ago
linkregister | a month ago
Eventually the companies that can't cope with undisciplined engineering will succumb to unacceptable reliability and be outcompeted, just like in the "move fast and break things" era.
vadepaysa | a month ago
I guess what I relate to the most is how dismissive people get about real software engineering work.
I may have skill issues, but I am yet to reach the level of autonomous engineering people tend to expect out of AI these days.
perching_aix | a month ago
Management is really pushing AI. It's obnoxious, and their idea on how it fits into my team's job specifically is completely, hilariously detached from reality. On the off chance someone says something reasonable, unless it fits the mold, it's immediately discarded. The mold being "spec driven development". We're not even a product team for crying out loud. I straight up started skipping these meetings for the sake of my sanity. It's mindwash, and it's genuinely dizzying. The other reason I stopped attending is because it ironically makes me more disinterested in AI, which I consider to be against my personal interests on the long run overall.
On the flipside, I love using Claude (in moderation). It keeps pulling off several very nice things, some of which Mitchell touched on in this post (the last one):
- I write scripts and automation from time to time; Claude fleshes them out way better with way more safety features, feature flags, and logging than I'd otherwise have capacity to spend time on
- Claude catches missed refactors and preexisting defects, and does a generally solid pass checking for defects as a whole
- Claude routinely helps with doing things I'd basically never be able to justify spending time on. Yesterday, I one-shotted an entire utility application with a GUI to boot, and it worked first try; I was beyond impressed.
- Claude helped me and a colleague do some partisan cross-team investigation in secret. We're migrating <thing> and we were evaluating <differences>. There was a lot of them. Management was in a limbo, unsure what to do, flip-flopping between bad options. In a desperate moment, I figured, hey, we kinda have a thing now for investigating an inhuman amount of stuff in detail - so I've put together a care package for my colleague with all our code, a bunch of context, a capture of all the input data for the past one week, and all the logs generated. Colleague put his team's side of the story next to it, and with the help of Claude, did some extremely nice cross-functional investigation. Over the course of a few weeks, he was able to confirm like a dozen showstopper bugs, many of which would have been absolutely fiendish if not impossible to fix (or even catch) if we went live without knowing about them. One even culminated in a whole-ass solution re-architecturing. We essentially tore down a silo wall with Claude's help in doing this.
So ultimately, it really is a mixed bag, with some really deep lowpoints and some really nice higlights. I also just generally find it weird that a technical tool [category] is being pushed down people's throats with a technical reasoning, but by management. One would think this goes bottom up, or is at least a lot more exploratory. The frenzy is real.
redwood | a month ago
zubspace | a month ago
Well, now you must to work with a confusing tool which slows you down. You are not allowed to use claude directly anymore, because someone heard that mythos is really bad for security. But hey, the tool integrates well with Jira!
You hate every second working with this thing. All the joy you had with explorative coding is forever gone, which was the sole reason you entered this field.
Deep inside you know that you can't change your job, because every other employer will cut its workforce as AI removes all manual labor of a software engineer and reduces risk to a minimum.
Oh, now we can finally move all those jobs to india without risk and shareholders will love it! How awesome is that! Wait, do we still need that guy in cubicle 42, who bitches and moans about AI every day? Nah...
nazcan | a month ago
In my case, it built a tool for splitting sounds and a tool for defining hitboxes for a game. Tools made exactly for more workflow. Wild times.
nunez | a month ago
In all seriousness...well, yeah. AI is a monkey's paw, and that's how monkey paws work. So many movies and books warned us!
DonHopkins | a month ago
crnkofe | a month ago
zmmmmm | a month ago
Purely AI written systems will scale to a point of complexity that no human can ever understand and the defect close rate will taper down and the token burn per defect rate scale up and eventually AI changes will cause on average more defects than they close and the whole system will be unstable. It will become a special kind of process to clean room out such a mess and rebuild it fresh (probably still with AI) after distilling out core design principles to avoid catastrophic breakdown.
Somewhere in the future, the new software engineering will be primarily about principles to avoid this in the first, place but it will take us 20 years to learn them, just like original software eng took a lot longer than expected to reach a stable set of design principles (and people still argue about them!).
uuyy | a month ago
Brian_K_White | a month ago
We didn't create the dna we rely on to produce food and lumber, we just set up the conditions and hope the process produces something we want instead of deleting all the bannannas.
Farming is a fine an honorable and valuable function for society, but I have no interest in being a farmer. I build things, I don't plant seeds and pray to the gods and hope they grow into something I want.
nradov | a month ago
Brian_K_White | a month ago
bluefirebrand | a month ago
If the farming situation were as dire as you seem to suggest, we'd have unpredictable famines all the time, but we don't
Brian_K_White | a month ago
Planting is merely setting up the conditions. We didn't write the dna, we couldn't write the dna if we wanted to because we are an infinity away from understanding all the actual processes that descend from the dna. And when we utilize the dna that we simply found and didn't and couln't hope to write, it's always, at best, a case of hoping it goes right again this time.
nradov | a month ago
Brian_K_White | a month ago
Even when it works, even if you put in a lot of work and experience and understanding, it still just worked by itself and it's just good luck every time.
You have also guessed incorrectly.
kibwen | a month ago
jcgrillo | a month ago
Scrape off all the soil, put it in casks, and bury it in a concrete bunker for 10000 years. Then relocate everyone and attempt to rebuild.
leoc | a month ago
Wow, it’s true, AI really is set to match human performance on large, complex software systems! ;)
detritus | a month ago
elictronic | a month ago
jimbokun | a month ago
ttoinou | a month ago
micromacrofoot | a month ago
ttoinou | a month ago
e9 | a month ago
ethbr1 | a month ago
TedDoesntTalk | a month ago
josephg | a month ago
Including all of the above.
Yokohiii | a month ago
rented_mule | a month ago
https://www.joelonsoftware.com/2000/04/06/things-you-should-...
A decade ago, I was sitting in on a meeting about a rewrite and, before I could say anything, someone in the first year of her career asked why anyone thought a rewrite would be any cleaner once all the edge cases were handled. Afterwards, I asked her where she learned this. She said "I don't know, it just seems kind of obvious." She went on to be a great engineer and is now a great manager.
tudelo | a month ago
steveBK123 | a month ago
Greenfield guy comes in, promises the world, and starts from some first principles white papered architecture. It's really lovely until they onboard the first user. Then they slowly commit all the "sins" (features that drive revenue) of the first system.
The firm is stuck supporting N systems indefinitely because the perfect new system takes so long to cover even 30% of the original system use cases, that management takes a flier on.. bear with me.. a second rewrite. Now they have 3 systems.
I've seen more 3rd systems than I've seen actual decommissioning of original systems into a single clean new system.
The answer is chipping away, modularizing, and replacing piecemeal Ship of Theseus style. But that does not drive big hires and big promotions.
monkpit | a month ago
Do they??
jplusequalt | a month ago
My team lead has worked on the same software for 30 years. He has the ability to hear me discuss a bug I noticed, and then pinpoint not only the likely culprit, but the exact function that's causing it.
DougN7 | a month ago
reassess_blind | a month ago
vasco | a month ago
And with one you need to train a guy for 25 years and with the other you need plan mode for a few minutes and then it runs 24/7.
jplusequalt | a month ago
vasco | a month ago
globalnode | a month ago
jimbokun | a month ago
jckahn | a month ago
vasco | a month ago
Then the only "experts" (not even close, just a guy with a form and some technical training) are the building inspectors who come at the end to verify if some stuff is done up to code.
Other than the original architect who draw the plans that got used for many buildings and the electrical engineer that cleared the electrical, no experts were involved. This is basically how the whole city and most of the country was built.
There's no expert mason or painter or whatever involved. Just a dude that can hold a paint roller. That's the same as going from a craftsman programmer to some dude with claude. Individual quality goes down, but more importantly price goes down way more and so many more people get access to much better quality than having nothing.
jimbokun | a month ago
And the equivalent for software. It’s usable, intuitive, responsive, stats up and running, and doesn’t leak my private data.
jplusequalt | a month ago
danparsonson | a month ago
jimbokun | a month ago
There is a lot of absurdly complex software that runs with high reliability. We hear a lot about the ones that don’t.
kiba | a month ago
jimbokun | a month ago
Younger implies cheaper.
devin | a month ago
I have really tried as an "old" person in the field to try and pass on the stuff I've learned, but "craft" and such really has absolutely no home in modern dev culture. The people who care about history, the craft, etc. are increasingly rare.
whateveracct | a month ago
maybe some that people said were that bad. but they just needed some elbow grease. remember, it takes guts to be amazing!
blipvert | a month ago
“ These are highly complicated pieces of equipment… almost as complicated as living organisms.
In some cases, they’ve been designed by other computers.
We don’t know exactly how they work.”
Now how did that work out ;-)
singlow | a month ago
blipvert | a month ago
thaumasiotes | a month ago
delichon | a month ago
orev | a month ago
aaron_m04 | a month ago
jeremyjh | a month ago
hennell | a month ago
dalmo3 | a month ago
AussieWog93 | a month ago
malfist | a month ago
maplethorpe | a month ago
jcgrillo | a month ago
stavros | a month ago
Violets are blue
AI is great
And so are you
missedthecue | a month ago
SpicyLemonZest | a month ago
literalAardvark | a month ago
SpicyLemonZest | a month ago
fg137 | a month ago
(None of above is theoretical)
ActorNightly | a month ago
Imagine the year is 1995, C exists, but some guy out there is working on essentially what modern Python is. He says to you "check out this language, you can just import stuff, and use it and dynamically modify anything at run time". You can probably come up with hundreds of arguments about things that could go wrong, like memory clean up, threading, e.t.c, but turns out, incrementally, they were all solved and we have the modern Python that basically is good enough to build these large LLM models.
Now imagine modern programming and computing is what C was back in 1995, and AI use is that guy building the Python code.
fg137 | a month ago
I think you have some serious misunderstanding here.
ActorNightly | a month ago
maplethorpe | a month ago
defrost | a month ago
The infill will look seamless.
And entirely lack any actual strikes of interest - the outliers are exceptional signal and the entire raison d'etre for building such a database.
Jeez, if AI can just infill where the gold is, why even bother to look in the first place.
jeremyjh | a month ago
Also, Python does not build or run large language models. It orchestrates C code that does that, and it was probably good enough to do that in 1998.
snovymgodym | a month ago
The biggest change that happened was that hardware kept getting better and it became feasible to use garbage-collected languages everywhere including really inefficient implementations like CPython.
That being said, 30 years later Python is still slow as shit even compared to other dynamic languages and runs into all kinds of scaling issues when used for anything serious. And everywhere that performance matters, software continues to be written in typed, compiled languages including C (but also C++, Rust, Go, etc.). Even in ML, Python chiefly acts as a thin wrapper and glue language for high performance CUDA libraries (aka C and C++).
So your historical analogy is mostly anachronistic.
ActorNightly | a month ago
In the future, you won't be dealing with strings, json, or apis. You will be importing agents, and giving them brief instructions, either in plain English or in some intermediate language higher than Python that is more brief. Wanna deal with database reliability ? Import database agent and give it brief instructions on what you want to manage. Just like you mention, right now Python is the wrapper for low level libraries, because everyone who is doing work in ML doesn't want to waste time making sure their C Cuda kernels compile. In the same way, nobody is going to care if they get the API headers right, or if their strings are correctly parsed when you can just invoke a dedicated LLM (which will likely be highly specialized small model able to run on local hardware) to do all that.
You can scream and cry as much as you want how that is bad, how its slow, but nobody is going to care because shit is going to get built faster. Ever notice how despite the massive layoffs across tech, there isn't service degradation in any sector? Good luck trying to sell your Rust skills in the future lol.
jcalx | a month ago
[0] https://news.ycombinator.com/item?id=48037128#48038639
[1] https://en.wikipedia.org/wiki/Peter_principle
thefourthchime | a month ago
It doesn't know what mess you want to clean up. A lot of times AI just starts making up new patterns on top of other patterns and having backwards compatibility between the two. How does it know which one you actually like?
ramoz | a month ago
jeremyjh | a month ago
slopinthebag | a month ago
pjc50 | a month ago
tosti | a month ago
the13 | a month ago
jeremyjh | a month ago
The reason Oracle can continue failing at those massive projects is simple: everyone fails at them routinely and often it’s the customers fault.
ocdtrekkie | a month ago
namtab00 | a month ago
It's just an umbrella term for "weak process glue code".
johnnyanmac | a month ago
It's even simpler. Youre not paying oracle for some delapidated HR system. You're paying for the legion of accountability that is their on-site engineers to fix stuff for you when things screw up. You're essentially subscribing to a team of engineers you don't need to directly pay salary and benefits to.
People who think you can out efficiency that kind of accountability don't understand how large orgs think.
billywhizz | a month ago
it will kill all the people in that hospital too
rcoveson | a month ago
jatora | a month ago
salawat | a month ago
ryandrake | a month ago
ro_bit | a month ago
> On January 3, 2022, the jury found Holmes guilty on four of the seven counts related to defrauding investors: three counts of wire fraud, and one of conspiracy to commit wire fraud. She was found not guilty on four counts related to defrauding patients
Dylan16807 | a month ago
jameshart | a month ago
jcgrillo | a month ago
linkregister | a month ago
GolfPopper | a month ago
ethbr1 | a month ago
What do you think the fake Delve attestation scandal was about? https://news.ycombinator.com/item?id=47444319
yumraj | a month ago
ramoz | a month ago
johnnyanmac | a month ago
That sadly does seem to be the trajectory of 5-10 years from now, though. I can't speak to if "AI is the future" of 30+ years from now, but these coming years sounds rife for "janitors" to clean up all the slop being produced by newly empowered idea guys
tacostakohashi | a month ago
Definitely cleaning up other people's AI mess for them for free is not a good use of time.
technion | a month ago
(Screams in "deployed in 2026 a new product that only works in internet explorer" in healthcare).
evenhash | a month ago
EasyMark | a month ago
AlexCoventry | a month ago
jimbokun | a month ago
3form | a month ago
mikestorrent | a month ago
TheGrassyKnoll | a month ago
ofjcihen | a month ago
paulryanrogers | a month ago
_HMCB_ | a month ago
sir0010010 | a month ago
ActorNightly | a month ago
People really have a misconception about the sums of money that companies operate on on a regular basis. If you are a people person and know essentially how to sell yourself, you can "scrape" money on the fact that nobody is going to look or think too hard about some contract that represents a tiny fraction of the years budget.
wild_egg | a month ago
h317 | a month ago
all2 | a month ago
johnnyanmac | a month ago
ramoz | a month ago
hattmall | a month ago
ramoz | a month ago
jcgrillo | a month ago
It's really nowhere near as complicated as making distributed systems reliable. It's really quite simple: read a fucking book.
Well, actually read a lot of books. And write a lot of software. And read a lot of software. And do your goddamn job, engineer. Be honest about what you know, what you know you don't know, and what you urgently need to find out next.
There is no magic. Hard work is hard. If you don't like it get the fuck out of this profession and find a different one to ruin.
We all need to get a hell of a lot more hostile and unwelcoming towards these lazy assholes.
altairprime | a month ago
fooker | a month ago
Here’s a slightly different future - these AI rescue consultants are bots too, just trained for this purpose.
Plausible?
I have already experienced claude 4.7 handle pretty complex refactors without issues. Scale and correctness aren’t even 1% of the issue it was last year. You just have to get the high level design right, or explicitly ask it critique your design before building it.
malfist | a month ago
Do you think people are not giving their agents specs and asking for input?
fooker | a month ago
literalAardvark | a month ago
djeastm | a month ago
vasco | a month ago
iugtmkbdfil834 | a month ago
jgilias | a month ago
Doesn’t work well ofc in a one shot situation with no context.
kilroy123 | a month ago
- AI Hype
- AI Psychosis
- AI keeps getting better and better until it can work around big AI slop code bases
bluefirebrand | a month ago
The belief in this is a form of AI psychosis, I think.
Maybe in the future but certainly no evidence of this anytime soon
fooker | a month ago
Here's some anecdotal evidence from me - I cleaned up multiple GPT 4.x era vibecoded projects recently with the latest claude model and integrated one of those into a fairly large open source codebase.
This is something AI completely failed at last year.
Maybe you should try something like this or listen to success stories before claiming 'certainly no evidence' in future?
whimsicalism | a month ago
asveikau | a month ago
What evidence is there that we're not at or close to a plateau of what LLMs are capable of? How do you know the growth rate from 2023 to present will continue into 2029? eg. Is it more training data? More GPUs? What if we're kind of reaching the limits of those things already?
literalAardvark | a month ago
And the answer appears to be that the improvement is accelerating. So how could it be stopping?
https://metr.org/time-horizons/
mbgerring | a month ago
I don’t think that the current AI paradigm has infinite headroom for improvement, similar to how every other AI approach before it eventually hit a limit.
literalAardvark | a month ago
And the link I posted shows the amount of work a query can do increasing non linearly. You can explore the site for more detail and a graph that shows error rates getting halved every couple of months.
No one said anything about infinite. It doesn't mean we don't have headroom to spare.
Software itself took 80-120 years to get where it is today depending on how you count. Time is on AIs side here.
whimsicalism | a month ago
I don't see why we would assume that we are at a plateau for RL. In many other settings, Go for instance, RL continues to scale until you reach compute limits. Some things are more easily RL'd than others, but ultimately this largely unlocks data. We are not yet compute/energy/physical world constrained. I think you would start observing clear changes in the world around you before that becomes a true bottleneck. Regardless, currently the vast majority of compute is used for inference not training so the compute overhang is large.
Assuming that we plateau at {insert current moment} seems wishful and I've already had this conversation any number of times on this exact forum at every level of capability [3.5, 4, o1, o3, 4.6/5.5, mythos] from Nov 2022 onwards.
beej71 | a month ago
js8 | a month ago
The (leading) LLMs work by consensus, like Wikipedia, Openstreetmap, web search engine or opensource movement.
What I mean is if I ask LLM "create a linked list", its understanding (of what I want) is already close to the expected ideal. Just like Wikipedia article on linked list, for example.
But the LLMs will continue to improve in breath and depth of understanding the world, although technically (what they CAN do) they probably already peaked. Similarly, OSS movement technically peaked in the 90s with the creation of compiler, operating system and a database; doesn't mean that new opensource isn't being created.
gwerbin | a month ago
js8 | a month ago
LLMs (or specifically GPT algorithm) are 8 years old. It has matured as a technology. I am not sure how you imagine it being significantly improved, from a user point of view, without some kind of paradigm shift (i.e. something significantly different from GPT or LLM).
Although I can imagine one important social innovation yet to come - a generally available big public LLM, that "anybody can train". We had a technology of "encyclopedia" for years (famously Brittanica); yet the concept of Wikipedia has been a truly new take on encyclopedia.
Also, new kinds of AI might emerge - for example we might formalize all types of human reasoning and build a reasoning AI, as well a model of human language, from scratch rather by training via GPT (and thus, more understandable and potentially smaller). But that won't be an LLM.
gwerbin | a month ago
I proposed how. New harness techniques and new training data/techniques, so the harness gets better and the LLM can be trained to work better with the harness. There's no reason to believe we're out of momentum for improvement in that direction.
js8 | a month ago
However, they also make mistakes like humans, I don't think a better harness or better training will fix that, because fundamentally, they cannot read your mind, if you put in an ambiguous prompt.
I like to compare the process of turning inexact text to formal language to an error-correcting code. If you haven't made too much mistakes or have been precise in the specification, it will self-correct and do what you want. But if your input is too ambiguous, it will never do exactly what you want, but something close to it. And people (who are using AI) are still learning where is the boundary and how to tell.
The companies building these models are training them to react to typical expectations. If you have some special need, you will always have to tell the model, otherwise it will not know your exact context. And the harnesses have many tools for that or try to do that automatically already.
ashdksnndck | a month ago
1) same business logic implemented in two different places, with extra code to sync between them
2) fixing apparently simple bugs results in lots of new code being written
It’s a sign I need to at least temporarily dedicate more effort to overseeing work in that area.
I somewhat agree with the AI psychosis framing of the OP. It takes some taste and discipline to avoid letting things dissolve into complete slop.
asveikau | a month ago
* A belief that AI will keep getting better, presented without evidence, does not yield a lot of skepticism around these parts.
* Your comment saying it is wrong to believe AI will keep getting better, also presented without evidence, is downvoted.
jacobjjacob | a month ago
asveikau | a month ago
gwerbin | a month ago
I don't know what happens in a decade when there are no junior engineers, skilled senior engineers are becoming rare, and the only data left the train LLMs on is 200th-generation slop. But AI slop being qualitatively slop is not enough of a obstacle to prevent that future from coming to pass. And billions of dollars will be "saved" along the way.
johnnyanmac | a month ago
That's what makes this whole house of cards dangerous. The prescription to psychosis is profitable. Aka, selling a grift.
user34283 | a month ago
I instructed it to split it up anyway, yet I wonder how often the concerns around the mess are imaginative rather than practical.
mattmanser | a month ago
That's serious levels of circular thinking right there.
fooker | a month ago
We train humans to do things untrained humans can not do.
mattmanser | a month ago
That's not at all how AI training works.
bigstrat2003 | a month ago
dullcrisp | a month ago
fooker | a month ago
Commits, design reviews, whitepapers, code reviews, test suites. And pretty concerning : chat logs and even keystrokes from employees nowadays.
The way we train specialized bots now is incredibly inefficient, that part is rapidly improving.
jiggawatts | a month ago
I thought the same when I saw development outsourced to Indians that struggled to write a for loop.
I was wrong.
It turns out that customers will keep doubling down on mistakes until they’re out of funds, and then they’ll hire the cheapest consultants they can find to fix the mess with whatever spare change they can find under the couch cushions.
Source: being called in with a one week time budget to fix a mess built up over years and millions of dollars.
jimbokun | a month ago
bombcar | a month ago
alhazrod | a month ago
abhiyerra | a month ago
I think the problem will get worst. I dislike the marketing around AI, but I do think it is a useful tool to help those who have experience move faster. If you are not an expert, AI seems to create a complex solution to whatever it is you were trying to do.
ethbr1 | a month ago
I've been watching non-developers vibe code stuff, and the general failure mode seems to be ignorance of 3-pick-2 tradeoffs.
They'll spam "make it more reliable" or some such, and AI will best-effort add more intermediary redis caches or similar patterns.
But because the vibe coders don't actually know what a redis cache is or how it works, they'll never make the architectural trade-offs to truly fix things.
danbolt | a month ago
I often wonder if it’s the statistical nature of the LLM mixed with a request in the prompt.
suzzer99 | a month ago
hughw | a month ago
I exaggerate only a little.
Jagerbizzle | a month ago
jimbokun | a month ago
djeastm | a month ago
thefourthchime | a month ago
gerdesj | a month ago
You have not seen the spreadsheets that accounts run the firm on.
Bloody kids!
whimsicalism | a month ago
Aperocky | a month ago
Are you sure about this? Yes, there is a stable set, but they are used in all of the wrong places, particularly in places where they don't belong because juniors and now AIs can recite them and want to use them everywhere. That's not even discussing whether the stable set itself is correct or not - it's dubious at this point.
hgs6 | a month ago
jimbokun | a month ago
digitaltrees | a month ago
jimbokun | a month ago
digitaltrees | a month ago
therealdrag0 | a month ago
jatora | a month ago
m101 | a month ago
spamizbad | a month ago
m463 | a month ago
I think it will be needless verbose complexity.
I kind of imagine someone having an unlimited budget of free amazon stuff shipped to their house.
In theory, they are living a prosperous life of plenty.
In reality, they will be drowning in something that isn't prosperity.
CamperBob2 | a month ago
The explanation, in turn, can be fed back to recreate the functionality of the original code.
At that point, why care about the code at all? If it works, it works. If it doesn't, tell the model to fix it. You did ask for tests, right?
That is where we're indisputably headed. It's not quite a lossless loop yet, but those who say it won't or can't happen bear a heavy burden of proof.
xstas1 | a month ago
On one end, you have code that can perform only the behaviour explicitly declared in the spec, but has to be thrown away and rewritten for any new or updated spec.
On the other end, you have code that implements or anticipates a wide range of future possible specs including the given one.
The AI can operate on any point on this spectrum, but it's not very good at choosing. The more complex the software, the more such choices need to be made.
When the number of bad choices reaches a certain critical mass, even a skilled engineer becomes powerless to undo all the bad choices, and even a powerful model becomes unable to reduce it back to a coherent spec.
m463 | a month ago
Some people are mindful about what they get and don't get from amazon and don't die from prosperity. ("you might use AI to increase your prosperity")
the rest of the world eats too much and dies of heart disease/diabetes. ("the rest of the world will flounder more and AI will do more stuff to them than for them")
onlyrealcuzzo | a month ago
In their current forms, it's unlikely for a product that actually needs to work.
It's not getting that complex and working with current LLMs.
reverius42 | a month ago
badtuple | a month ago
The issues have all been structural, not local. It's easier to treat it like a rewrite using the original as a super detailed product spec. Working on the existing codebase works, but you have to aggressively modularize everything anyway to untangle it rather than attack it from the top down.
All of these projects have gone well, but I haven't run into a case where a feature they thought was implemented isn't possible. That will happen eventually.
It's honestly good, quick work as a contractor. But I do hope they invest in building expertise from that point rather than treating it like a stable base to continue vibecoding on.
hattmall | a month ago
badtuple | a month ago
The greatest asset in this type of work is genuinely liking people, being good at what you do, and keeping in touch. My email is easily findable for a reason.
johnnyanmac | a month ago
The one part I do wonder is how to "keep in touch". Maybe it's a generational thing as a young millennial (some would call it "Zillenial") but the biggest issue in my networking over the year (cough and the dating scene cough) is ghosting. You think you hit it off, try to follow up the day after, and proceed to never again hear from them.
luxuryballs | a month ago
dboreham | a month ago
taurath | a month ago
andsoitis | a month ago
But won’t those more complex systems presumably solve more complex problems than the systems that humans could build? Or within a comparable time?
I think it is reasonably safe to assume at this point in the game that these AI systems are increasingly able to reason rigorously about novel problems presented to them, of ever increasing complexity and sophistication.
CoderKatrina | a month ago
fractallyte | a month ago
https://www.hypercubic.ai/hopper
thefourthchime | a month ago
Ultimately, if you want to move fast, it's better just to have one engineer vibe coding something. but, that engineer is under so much pressure. Now he's got a legacy mode and another legacy mode because the requirements keep changing. And now there's a deadline in four weeks.
This all could work just fine, but the ungodly amount of attention that this world is getting puts too many cooks in the kitchen, which is always a recipe for disaster.
singpolyma3 | a month ago
rini17 | a month ago
aeve890 | a month ago
LogicFailsMe | a month ago
mrwaffle | a month ago
LAC-Tech | a month ago
I am very close to using it as a pair programmer, but with me actually coding. I am just so tired of fixing its mistakes.
nunez | a month ago
Probably from the EU because they seem to be the sane ones of this generation.
LAC-Tech | a month ago
mattbrewsbytes | a month ago
Sure there are industry changing things going on. What if you're working on an app thats a decade old and has had different teams of people, styles, frameworks (thanks to the JS-framework-a-week Resume Driven Development)? Some markdown docs and a loop of agents isn't going to help when humans have trouble understanding what the app does.
daneel_w | a month ago
gverrilla | a month ago
flumpcakes | a month ago
I really do worry - I especially worry about security. You thought supply chain security management was an impossible task with NPM? Let me introduce to AI - you can look forward to the days of AI poisoning where AIs will infiltrate, exfiltrate, or just destroy and there's no way of stopping it because you cannot examine the internals of the system.
AI has turbo charged people's lax attitude to security.
God help us.
mintplant | a month ago
Some time down the line, I discover CPU being maxed out, which is showing up in degraded performance in other parts of the system. I investigate, and I trace the issue to a boneheaded busy loop in this library that no human with the domain expertise to implement the library would have written. Turns out I'd missed one deeply-buried mention in the README that maintenance was being done via AI now, and basically the whole library had been rewritten from the ground up from the reliable tool it used to be to a vibecoded imitation.
Yeah, yeah, sure, bad libraries existed before all this. But there used to be signals you picked up on to filter the gold from the dreck. Those signals don't work anymore.
The_President | a month ago
topherPedersen | a month ago
apalmer | a month ago
It is definitely factual that there is a complete paradigm shift in the prioritization of quality in software. It's beyond just AI side effects, and now its own stand alone thing.
There have always been many industries, companies, and products who are low on quality scale but so cheap that it makes good business sense, both for the producer and the consumer.
Definitely many companies are explicitly chosing this business strategy. Definitely also many companies that don't actually realize they are implicitly doing this.
Wether the market will accept the new software quality paradigm or not remains an open question.
matt3210 | a month ago
Apocryphon | a month ago
tamimio | a month ago
But in reality, anyone who knows their field and are going after certain specific issue, they will find soon how AI is nothing but an assistant, sure it can help and automate some stuff, but that’s it, you need to keep it leashed and laser focused on that specific issue. I personally tried all high end ones, and I found a common theme, they are designed to find a solution or an answer no matter what, even if that solution is a workaround built on top of workarounds, it’s like welding all sort of connections between A and B resulting in a fractal structure rather than just finding a straight path, if you keep it going and flowing on its own, the results are convoluted and way over complicated, and not the good complexity, the bad kind.
the13 | a month ago
You should not release a product into the market unless you have a good enough product that can keep you and your client compliant, safe and secure - including not leaking their customer info all over the place.
Prompt injection risk, etc. are massive for agentic AI without deterministic guardrails that actually work in practice.
Stop testing in production if you're shipping in a regulated industry. Ridic!
If you're not technical, you can get someone who is after signs of p-m fit, demos, but BEFORE deployment. This is common sense and best practices but startup bros dgaf because they're just good at sales and marketing & short term greedy.
Comical.
Ifkaluva | a month ago
madrox | a month ago
What's more, the only people they talk to about it are others at the same company. There is no external touchstone. There are power dynamics from hierarchy. No new ideas other than what is generated within the company. In other circumstances, this is a textbook environment for radicalization.
I would encourage all leadership to take a deep breath. You have time to think slow.
dudul | a month ago
You first use the full words and then introduce the acronym that you're going to use in the rest of the text: "Mean Time Between Failures (MTBF) vs. Mean Time to Recovery (MTTR)".
With the latter, readers understand the term immediately, even if they don’t know the acronym. And they don't have to read these weird letters before getting the explanation.
mmaunder | a month ago
whimsicalism | a month ago
keepamovin | a month ago
“It feels like entire companies are deluded into thinking they don’t need me, but they still need me. Help!”
The broad sentiment across statements of this “AI psychosis” type is clear, but I think the baseline reality is simpler. How can you be so certain it’s psychosis if you don’t know what will unfold? Might reaching for the premature certainty of making others wrong, satisfying that it might be to the ego, be simply a way to compensate the challenges of a changing work environment, and a substitute for actually considering the practical ways you could adapt to that? Might it not be more helpful and profitable to consider “how can I build windmills, ride this wave, and adapt to the changing market under this revolution” than soothing myself with the delusion that all these companies think they don’t need me now, but they’ll be sorry.
The developer role is changing, but it doesn’t have to be an existential crisis. Even though it may feel that way — but probably it’s gonna feel more that way the more you remain stuck in old patterns and over-certainty about how things are doesn’t help, (tho it may feel good). This is the time to be observant and curious and get ready to update your perspective.
You may hide from this broad take (that AI psychosis statements are cope) by retreating into specific nuance: “I didn’t mean it that way, you’re wrong. This is still valid.” But the vocabulary betrays motive. Resorting to clinical derogatory language like “AI psychosis” invokes a “superior expert judgment” frame immediately, and in zeitgeist context this is a big tell. It signifies a need to be right, anda deeply defensive pose rather than a clear assay of what’s real in a rapidly changing world. The anxiety driving the language speaks far louder than any technical pedantry used to justify it, and is the most important and IMO profitable thing to address.
hoppp | a month ago
A lot of companies have been under AI psychosis for years and will be forever.
JeremyJaydan | a month ago
awesomeusername | a month ago
Sorry, I don't buy your argument
charlotte-fyi | a month ago
I think Mitchell's point is well taken -- it's possible for these tools to introduce rotten foundations that will only be found out later when the whole structure collapsed. I don't want to be in the position of being on the hook when that happens and not having the deep understanding of the code base that I used to.
But humans have introduced subtle yet catastrophic bugs into code forever too... A lot of this feels like an open empirical question. Will we see many systems collapse in horrifying ways that they uniquely didn't before? Maybe some, but will we also not learn that we need to shift more to specification and validation? Idk, it just seems to me like this style of building systems is inevitable even as there may be some bumps along the way.
I feel like many in the anti camp have their own kind of reactionary psychosis. I want nothing to do with AI but I also can't deny my experience of using these tools. I wish there were more venues for this kind of realist but negative discussion of AI. Mitchell is a great dev for this reason.
doginasuit | a month ago
denkmoon | a month ago
doginasuit | a month ago
somewhatgoated | a month ago
“right tool for the job” - what job exactly, why so mysterious?
doginasuit | a month ago
Planning: I often ask it to help me plan an approach if we are dealing with something I don't have a lot of experience with, most recently working with the DOM. If there is a library or an API that is new to me, I ask for an overview and run my plan by it for comments. Feed it the documentation and it is like talking to author.
Coding: I have a pretty reliable sense for when a section of code that I want to write is obvious enough for the LLM to one-shot based on the other code in the file, and on those occasions I call in completion. I do this with code that I can verify at a glance.
Analysis: If I have any uncertainty at all about the code I've written, I run it by the LLM to find issues. Out of all the other uses, I think this is the most productive and time saving. If I run into a bug and I'm stumped, I show it the section of code. I'm amazed at how good it is at finding mistakes.
I'm working solo as a full stack developer coming from a different background, so I sometimes find myself out of my depth. Having access to the breadth of knowledge that an LLM brings and its attention to detail has been game changing. I've tried a couple agents and configuring them to work competently seems like a rabbit hole, and I like the tight control over the context that chatting with the web prompt interface brings. It seems like half the value is putting into words my intent, it forces me to have a cohesive understanding myself. It is like rubber duck debugging where the duck can actually talk back and sometimes provide the critical part that I'm missing. I have it speak like a pirate which is just for fun but sometimes the sailing metaphors that it uses are really intuitive.
somewhatgoated | a month ago
Weebs | a month ago
I ran into an issue where I was getting a segfault and everything looked right in the debuggr, including expected values near the segfault. Turns out I wasn't using placement new somewhere I needed, and the data for the object was getting copied but not the vtables. I have no idea how long it would have taken me to figure that out on my own because the segfault was coming from so far away
I haven't had the opportunity to use LLMs much for coding since I'm not working right now, but I can second how much of a boost just getting specific answers to my questions instead of reading tons of whatever online searches return is.
Rubber duck that talks back is a nice way to put it
zemo | a month ago
achenet | a month ago
It used to be "oh, why am I getting an error on line 352, let me google the error message and wade through Stack Overflow answers" now it's "Claude, why am I getting an error on line 352? Ah, it's because $REASON, let's see if that fixes it, yes, thank you."
Obviously reading the official documentation is very useful, but sometimes you can't find anything that relevant to your exact use case, and forums are also very useful, but it can take hours or even days to get a reply to question when the LLM can do it in like a minute.
IX-103 | a month ago
If I ask it to me produce a design, I'll almost always end up with something unworkable or inefficient.
Though if you push it hard enough then it can sometimes give you a good description of what existing code does and how it does it (which can be easily verified).
sph | a month ago
Every thread is endless back-and-forth between the "AI works great and vibe coding is the future" and "no, AI works great as long as you don't vibe code" camps.
mkhpalm | a month ago
radlad | a month ago
zzrrt | a month ago
So now the AIs will do more of that, at superhuman speed.
> will we also not learn that we need to shift more to specification and validation
We'll just quickly learn what we've been trying to do for decades, while also treading water in floods of more code than has ever been written before? And some of the motivations to write correct code are being deflated - "just vibecode it again and see if the bugs disappear, it only took a week and $200."
DoctorOetker | a month ago
Currently the bugs are found by people using LLM's but aren't the developers. As more projects start getting access to compute, they can run those LLM searches for bugs themselves, and can simply prevent shipping the bugs.
I'm surprised no one has tried making any statistical analysis of bug densities, and "bug authors" in an attempt to identify untrustworthy developers, regardless of intent. Given a dataset of authors and prior bugs, it may help find more bugs by tracking their pull requests with higher scrutiny...
Some people may end up with an eternal stain if they've been taking money to submit vulnerable code to code bases...
johnnyanmac | a month ago
You're using psychosis wrong. My literal reality is my entire industry trying to use Ai as an excuse to payoff hundreds of thousands, to millions of American engineers in lieu of outsourcing work overseas. It's having hostile promots to use AI that never truly go away (if you're even given an option to turn off the prompt). It's seeing an emerging generation completely stunted because AI's best use is to cheat the education system and ruin the youth's critical thinking. It's looking in apallment at proposals for data centers that take more energy than the state actually has.
And while you can try to call these exaggerations, you're falling into the very psychosis of this article if you want to deny this reality as a whole. "but the tech is making us so productive" is not a valid justification to literally collapse human society as we know it.
viccis | a month ago
Also "reactionary" haha
foxfired | a month ago
Right know, prompters are setting up whole company infrastructure. I personally know one. He migrated the companies database to a newer Postgres version. He was successful in the end, but I was gnawing my teeth when he described every step of the process.
It sounded like "And then, I poured gasoline on the servers while smoking a cigarette. But don't worry, I found a fire extinguisher in the basement. The gauge says it's empty, but I can still hear some liquid when I shake it..."
If he leaves the company, they will need an even more confident prompter to maintain their DB infrastructure.
consumer451 | a month ago
Oh man, I think you may have touched the third rail here.
My first job out of high school was as an AutoCAD/network admin at a large Civil & Structural firm. I later got further into tech, but after my initial experience with real Engineering, "software engineering" always made my eyes roll. Without real enforced standards, without consequences, it's been vibe engineering the whole time.
In Civil, Structural, and many other fields, Engineers have a path to Professional Engineer. That PE stamp means that you suffer actual legal consequences if you are found guilty of gross negligence in your field. This is why Engineering firms are a collective of actual Professional Engineer partners, and not your average corporate structure.
The issue is that in software dev, we move fast, SOC2 is screenshot theater, and actual Engineering would slow things way down. But, now that coding is fast, maybe you are correct! Maybe vibe coding is the forcing function for actual Software Engineering!
___
edit: I just searched to see if my comment was correct, and it turns out that Software PE was attempted! It was discontinued due to low participation.
> NCEES will discontinue the Principles and Practice of Engineering (PE) Software Engineering exam after the April 2019 exam administration. Since the original offering in 2013, the exam has been administered five times, with a total population of 81 candidates.
https://ncees.org/ncees-discontinuing-pe-software-engineerin...
SequoiaHope | a month ago
This was something I noticed in my early career in mechanical engineering and later doing PCB design and software for robotics. It’s easy to find firms that just need adequate parts without the professional certifications or ass-covering calculations of other engineering fields.
All this to say, it’s not just software versus the rest of them. From my position, civil and aerospace seemed more like the exception while much of the rest of the engineering world is more vibes based.
consumer451 | a month ago
dymk | a month ago
hliyan | a month ago
hliyan | a month ago
consumer451 | a month ago
I hope that this becomes a thing in Software Engineering.
Applejinx | a month ago
JayShower | a month ago
popcorncowboy | a month ago
Until and unless software is held to that standard, software will never be engineering and always just a craft that can be performed to any or no standard.
andoando | a month ago
Im sure for the most part, engineers in physical space deal with the same kind of tradeoffs software engineers make, where you try your best based on industry standards, personal past experiences without some way to prove what youve done is right
bigfatkitten | a month ago
That’s a relatively small field within the software industry.
Most of the work being done (adding new fields to CRUD apps etc) is glorified clerical work, where the people doing it are rightfully fearful of being automated out of existence by AI.
humanizersequel | a month ago
So it sounds like it was fine? Why would this prompt (haha) a change in their approach to things?
eddythompson80 | a month ago
That’s basically every M2, and many if not most M1s, in the last 10 years. So fuck it. Why does any of it matters?
shridharxp | a month ago
tns_admin | a month ago
I have seen people write highly complex code where all the complexity was not necessary. Think: deep unnecessary branching, pointless error handling and retries which make no sense in our context, hand-coded parsing using regexps, haphazard data flow, functions which seem purely computational but slyly make API calls, pointlessly nullable model fields, verbose doc comments which describe the implementation instead of the contract. I could go on.
The worst part is, even when "prompted" by bad coders, it works in the end. Even has tests (ostensibly mock-ridden, a pet peeve of mine which always falls on deaf ears). So I cannot reject the PR without being an asshole.
I am no luddite. I make heavy use of AI, with all the skills / AGENTS.md / style guides and clear specs, then review every line of code, prefer testing with minimal mocking. I'd even say with right prompting, it can write better low level code than me (eg: anticipating common error conditions).
But my biggest fear about AI is how it enables normies with little to no understanding of CS principles to produce code faster which looks correct but slowly poisons the codebase.
LPisGood | a month ago
Talking to him, he told me he couldn’t even reverse a string. He is at once many times more valuable than ever before to his company, but also far more dangerous than ever before.
CSSer | a month ago
gruzzlymug | a month ago
If you get the logs you can feed them in and ask for improvements, that sometimes helps.
CSSer | a month ago
anal_reactor | a month ago
skywhopper | a month ago
bigstrat2003 | a month ago
tns_admin | a month ago
As others have elaborated, the problem is empowering them to ship mountains of bad code;
And yeah, many semi-technical M2s or even M1s can't distinguish bad code from good code, or worse bad architecture from good; this is golden time for those who are willing to sacrifice the future for present. Just burnnn'em tokenzzz.
epolanski | a month ago
I would've believed that 6 months ago, but not now.
If you have a good codebase with proper rails, hygiene and architecture, AI will produce better code than most engineers out there.
People forget that 90% of the field has always been charlatans barely able to implement a fizz buzz or go much beyond trial and error googling.
I'll say even more. I'm in the 10%, and it's increasingly clear to me that AI writes in minutes code that's better than mine.
Even stellar and respected OSS engineers are nowadays leveraging AI and guiding it less and less everyday beyond giving indications of what kind of data structure they may want for a complex problem or the kind of architecture they are looking for.
In any case, I don't like this field anymore, I have no joy from it, way too much work, way too many changes a human can cope with both on product and technological level (not even counting AI and its tooling itself). The interesting parts of thinking an entire afternoon or week experimenting to get that design right disassembling the pros and cons are gone.
Even if you want to do that, it's just faster to launch 6/7 worktrees with the different ideas and judge the results. But you don't get as intimate with the problem and the amount of information is way more than you can process.
lbrito | a month ago
epolanski | a month ago
thoman23 | a month ago
AI: "I LEARNED IT FROM YOU, DAD!"
bigstrat2003 | a month ago
all2 | a month ago
gw32 | a month ago
johnnyanmac | a month ago
Okay, so Ai is completely useless in my industry. Got it.
jagenabler2 | a month ago
This is what I’m seeing, anyways. Junior engineers are being rewarded for shipping so much code, it’s impossible to evaluate it all, and subtle changes in existing patterns are slipping through. Eventually all those subtle changes transform the rails.
tns_admin | a month ago
This means you take less time reviewing code than it took for the machine to churn it out. All that code must be a ticking time bomb.
dawnerd | a month ago
gw32 | a month ago
eddythompson80 | a month ago
I think it’ll be the opposite. Maybe it’ll be what will eventually cement the field as “talent” based field. Just like it was difficult to quantify what makes a flute player better than another, how good your are at endlessly prompting a blackbox machine would be the only measure. The engineers of ol’ whoe developed kernels and drivers would be thought of as the “crazy people who put the flute against their temple to tune it” LOL. we don’t need people like that. You can just buy a flute tuning device. who gives a fuck? Can you make the next “Shake it, Shake it”?
xyzal | a month ago
heartbreak | a month ago
ozgrakkurt | a month ago
You can see the same approach is taken by Trump and other people.
“You have TDS!! He is actually doing good. He doesn’t follow rules because the system is rigged etc.”
These arguments border on religion because it is predicated on you believing their ignorant point of view in the first place.
Engineering and science is built on rigor and empirical evidence, it is not built by scammers/businessman/ignorant-people/politicians because that is just not how it works
jimbokun | a month ago
Even before LLMs generating entire programs, complex frameworks allowed developers to write the initial versions of programs very quickly, but at the cost of being hard to understand and thus hard to debug or modify.
Some of us are betting that the AIs will always be smart enough to debug, maintain and modify the programs written by AI, no matter how convoluted or complex. I’m not so sure.
sph | a month ago
Glyptodon | a month ago
coffeefirst | a month ago
insane_dreamer | a month ago
I cautioned them that this a terrible idea -- you have business people who don't know what they're talking about, and all they know if "if we don't 'do AI' we'll be left behind because our competitors are 'doing AI'" (whatever tf "doing AI" means).
Yes, LLMs are a great tool. But they're not like some magic bullet you stick into everything. Use it where it makes sense, and treat it like you would other tools.
You make "doing AI" some kind of KPI in your org, and you're going to have people "doing AI" amazingly (LOC counts! tokens burned! tickets cleared!) while not actually being more productive, and potentially building something that is going to come down on your head for the next team to "clean up the AI mess".
nwah1 | a month ago
sometimelurker | a month ago
puttycat | a month ago
sometimelurker | a month ago
- Nuggesting improvements to the code after finishing the task you gave it, very irritating when the improvements were obvious and the ai didn't implement them on its own
- Not trying very hard when implementing something, leading to bugs, which leads to more tokens used (this behavior can be incentivized and learned with RL)
Since its a known fact if a user continues a session after the LLM says something, its not hard to train against this. The least efficient way to do this would be to GPRO directly against the user base and try to get as many people talking to the AI, and with OAI having a billion monthly active users the least efficient method would work really well for them.
thr0w | a month ago
ByThyGrace | a month ago
sheepscreek | a month ago
In any case, this is what blue-green deployments and gradual rollouts are for. With basic software engineering processes, you can make your end user experience pretty much bullet proof. Just pay EXTRA attention when touching DNS, network config (for core systems) and database migrations.
Distributed systems are a bit more tricky but k8s and the likes have pretty solid release mechanisms built-in. You are still doomed if your CDN provider goes down. You just have to draw a line somewhere and face the reality head on (for X cost per year this is the level of redundancy we get, but it won’t save us from Y).
The one thing I hadn’t mentioned - one I AM worried about - is security! I’ve been worried about it from before Mythos (basic prompt injection) and with more powerful models now team offence is stronger than ever.
jnwatson | a month ago
teeray | a month ago
There’s this delusion that if we somehow write enough tests that we’ll expunge every defect from software. It’s like everyone forgets that the halting problem exists.
gregjor | a month ago
AI coding swept over the software industry faster than most previous trends. OOP and its predecessor "structured programming" took a lot longer. Agile and XP got traction fairly quickly but still took longer than AI -- and met with much of the same kind of resistance and dire predictions of slop and incompetence.
AI tools have led to two parallel delusions: The one Mitchell Hashimoto describes, and the notion that we (programmers) knew how to produce solid, reliable, useful, maintainable code before AI slop came along. As always with tools that give newbs, juniors, managers some leverage (real or imagined) we -- programmers -- get upset and react to the threat with dire warnings. We talk about "technical debt" and "maintainability" and "scalability."
In fact the large majority of non-trivial software projects fail to even meet requirements, much less deliver maintainable code with no tech debt. Most programmers don't know how to write good code for any measure of "good." Our entire industry looks more like a decades-long study of the Dunning-Kruger effect than a rigorous engineering discipline. If we knew how to write reliable code with no tech debt we could teach that to LLMs, but instead we reliably get back the same kind of mediocre code the LLMs trained on (ours), only the LLMs piece it together faster than we can.
With 50 years in the business behind me, and several years of mocking and dismissing AI coding whenever someone brought it up, I got dragged into it by my employer. And then I saw that with guidance and a critical eye, reasonably good specs, guardrails, it performed just as well and sometimes more throroughly than me and almost all of the people I have worked with during my career. It writes better code and notices mistakes, regressions, edge cases better than I can (at least in any reasonable amount of time).
AI coding tools only have to perform better -- for whatever that means to an organization -- than the median programmers. If we set the bar at "perfect" they of course fail, but so do we. We always have. Right now almost all of the buggy, insecure, ugly, confusing software I use came from teams of human programmers who didn't use AI. That will quickly change and I can blame the bugs and crashes and data losses and downtime on AI, we all can, but let's not pretend we're really losing ground with these tools or that we could all, as an industry, do better than the LLMs, because all experience shows that we can't.
jpease | a month ago
“very resilient catastrophe machine”
agnosticmantis | a month ago
What's the historical context for this MTBF vs. MTTR reckoning?
bastawhiz | a month ago
If you optimize for MTTR, you don't care how often you go down and instead optimize your recovery time to be as short as possible.
The concepts are pre-computing.
sebmellen | a month ago
tonymet | a month ago
MTTR = optimize the ability to correct failures when they occur.
He's describing leaders who believe quality no longer matters because any faults or deviations can be corrected so quickly that it doesn't make any sense to waste time on quality.
eddythompson80 | a month ago
- What alerts are we missing that could have helped us catch that earlier?
- What dashboards could we have had to help diagnose the issue quicker?
- What Ops tools could we have had to help mitigate such issue quicker?
- What extra logging/metrics/telemetry could we add to help us catch this quicker?
- What “safe deployment practices” could we have employed to avoid/improve this?
- what processes could we enforce to facilitate all of that?
Rinse and repeat that few hundreds or thousands of times while mounting MTTR KPI and you will see that number improve. Most likely through your team “gaming it”
MTBF is much, much, tricker to measure or “manage out”. It’s about “excellence in engineering” which is not measurable nor controllable. You want a random feature X. Your team tells you it’s really not how the system works, and they want few months making the change slowly while observing the system. But you don’t want just X, you want X, Y, Z, W, V, Q, A, B, C, D, all the way throw AAZZW12. So you tell the team to go fuck itself.
wiseowise | a month ago
shridharxp | a month ago
eddythompson80 | a month ago
Current (and by current I mean the last 4-5 years) they only cared about MTTR. That was probably the only metric they measured and cared about. When a system went down it fired an LSI “Live Site Incident” (as opposed to a CRI “Customer Reported Incident”). At the time you grilled your team. Eventually you come to the conclusion that an LSI should only be measured by MTTR. MTBF is meaningless because MTBF limits your “ship new features” velocity.
You might scoff at GitHub and “ship a new feature” concept in the last 5 years, but if you’re an enterprise customer you’d know how much nonesense they shoveled out in the last 5 years. Absolute insanity of “what the fuck” type feature because customer X who is paying $$$ is asking for it type features.
rethab | a month ago
John Allspaw (previously CTO at Etsy) has written about this: https://www.kitchensoap.com/2010/11/07/mttr-mtbf-for-most-ty...
kseniamorph | a month ago
wesselbindt | a month ago
heohk | a month ago
lordmoma | a month ago
HNisCIS | a month ago
Have you ever been in an HN thread where you're an SME on the thread topic and just been horrified by the confidently incorrect nonsense 90% of the thread is throwing around? Welcome to the training set motherfuckers.
LLMs do the same thing for what should be obvious reasons. If you search things that have some depth and you know the answer you'll be flooded by how often the models will just vomit confident half truths and misrepresented facts. They're better than they used to be, not just lying whole cloth most of the time, but truth is an asymptotic thing, not an exponential one.
tonymet | a month ago
The only reason it worked has been expansive money policy and a larger share of the cost of goods being dumped into marketing value while manufacturing costs dropped abroad. so no one bothered to check.
imrozim | a month ago
itqwertz | a month ago
At the end of the day, we can only read so much and take on so much work before we bottleneck ourselves. Cognitive overload leads to burnout. Rumplestiltskin vibes with this AI stuff…
wg0 | a month ago
Can someone please remind and refresh my memory what this whole debate was with what arguments?
ActorNightly | a month ago
wg0 | a month ago
BrenBarn | a month ago
The groundwork for that was laid long ago with the idea of constant updates. It's been fine for years to ship bugs and rely on a rapid release cycle and constant pressure on users to upgrade everything all the time. To roll that back requires a lot more than toning down AI psychosis; it requires going back to a go-slow mindset where you actually don't release things until they're ready. It still needs to be done, but it's harder than just laying off the AI kool-aid.
germandiago | a month ago
I already took a couple of decisions. It will go wrong or well. But is was decided a year and a bit ago.
If you think the future will be different, stop doing the same you used to do the same way you used to do it.
My analysis is that the labour market will increasingly bargain salaries and will make pressure on you. So how safe is that compared to before? Maybe working for someone as an employed full time person is not the best thing you can do anymore.
shoopadoop | a month ago
david_blitz1 | a month ago
TonyStr | a month ago
I think the use of the word here is meant to invoke the vision of someone under heavy delusions or hallucinations, such as (what Hashimoto percieves as) the delusion that shipping more bugs is fine if AI can resolve them faster. To what extent this counts as delusion (and thereby psychosis) would depend on how deeply you believe that this and related opinions are wrong.
pojzon | a month ago
Thankfully most of those things are a very small percent of my overall work.
If its a big percent of your work -> you are in trouble friend.
ben_w | a month ago
Never mind code, what happens when the CEOs, or the investors, listen to the sycophantic voices of their LLMs?
I think it looks like every product becomes the next Juicero of its field.
trizoza | a month ago
I'm afraid to say this out loud internally because I'm afraid of the next round of layoffs and I want to keep my job. So I just keep on shipping at a high pace, building massive cognitive debt and hoping the agents will get so good in near future, that there won't be the need for understanding the codebase.
pbasista | a month ago
Agents might get better. But who will own the code and take responsibility for it? The AI agent? The company who created the AI agent?
If e.g. a car crashes and does not deploy its airbags because the AI agent made a mistake in the airbag code, will the manufacturer be able to shift the blame to OpenAI or Anthropic?
I do not think so.
And therefore I believe that no matter how good the AI agents will ever become, the ultimate responsibility for the code will always remain with the companies that create the code. Regardless of which AI tools they use.
I see no other way to bear that responsibility by the company than to have people internally who will be responsible. And those people, if they actually want to own that responsibility, would need to understand that code themselves, in my opinion. Because relying on a non-deterministic AI agent's vetting is fundamentally unreliable, in my opinion.
rwmj | a month ago
thisisit | a month ago
ares623 | a month ago
kubb | a month ago
ares623 | a month ago
0xpgm | a month ago
There are people who write important software that the world runs on, but they do it outside the 'industry'.
A real industry should be responsive to events of nature, or at least the market, not vibes.
_heimdall | a month ago
DonsDiscountGas | a month ago
somewhatgoated | a month ago
mavelikara | a month ago
Market is vibes! The price of something at a moment is, for example, what market participants collectively agree what the price of it should be.
ozgrakkurt | a month ago
hackthemack | a month ago
I wrote a while back, Most of the executives I have met really have no clue. They just go with what is being promoted in the space because it offers a safety net. Look, we are "not behind the curve!". We are innovating along with the rest of the industry.
https://news.ycombinator.com/item?id=46670190
mavelikara | a month ago
That is an uncharitable interpretation, IMO.
The CFO heard of a novel technique used by his peers in other companies, and they reported good results. He wants to try it within his organization too. As an executive, he is paid to (among other things) keep abreast of such developments in the industry and ensure that the organization he is leading is not caught flat footed in the market.
sph | a month ago
wrxd | a month ago
It’s not all useless but most of the days I think I would be more productive if some processes were streamlined rather than if I had to throw tokens at them and still fail.
Of all the showcases I’ve seen the best are the ones written by people assuming that the token bonanza will not last so they used AI to build tools they wished they had. AI used to build the tool but by no means used by the tool, so if/when token quota gets reduced we still have a functional tool.
utopiah | a month ago
solenoid0937 | a month ago
Leadership is not being dumb, at least on this topic. If your token usage is that low, you just aren't using AI that much (even if you think you are.)
haneul | a month ago
blazespin | a month ago
denkmoon | a month ago
zomglings | a month ago
skydhash | a month ago
Software is a big graph of interlocked rules. And if you can grasp the whole or the part you own (and you should be able to), it's often very easy to see the control points. You don't have a coding bottleneck anymore, you have a communication bottleneck[0]. Which is an organizational issue, not anything relevant to engineering.
[0]: See Naur's Programming as Theory Building and Brooke's Mythical Man Month.
est31 | a month ago
Sometimes AI overdoes things and it re-runs the whole testsuite because the tail command didn't have enough lines, but the other way round messes up the context so much so that in the end all that context is useless.
seanmcdirmid | a month ago
look_lookatme | a month ago
verdverm | a month ago
kortilla | a month ago
k4rli | a month ago
Sharlin | a month ago
"If you aren't donating at least your salary's worth of company money to another company every day, are you even working?"
mancerayder | a month ago
Miner49er | a month ago
sumeno | a month ago
upcoming-sesame | a month ago
peab | a month ago
eaglelamp | a month ago
> Before the doomers come in, you get $200 in API credits every month for claude -p usage. Usage counts against those API credits.
So which is it $300/day is trivial to consume or $200/month is a completely reasonable limit, it can't be both.
Drupon | a month ago
never_inline | a month ago
nfRfqX5n | a month ago
johnnyanmac | a month ago
ex-aws-dude | a month ago
Trying to crank out all the tools I never had time to build because I think we’re going to get cut off eventually
hosteur | a month ago
WickyNilliams | a month ago
Custom lint rules to encode best practices that previously relied on astute/alert code reviewer to call attention to. This is handy not just for humans but it steers the bots too. Or turning on some existing rule that required a big cleanup/migration to be compliant with. Now I just throw an LLM at it, since they're often laborious but mechanical changes. Which is the sweet spot for an LLM.
Also automating everything I can. That annoying release process that everyone hates but wasn't quite long/arduous enough to justify the time before? It's now automated. GitHub workflows for all the things.
This kind of stuff will forever be useful, even if the bottom drops out and the bubble bursts. And none of it is reliant on AI to run
caarmen | a month ago
I feel like an imposter here, I’m definitely not using AI as much as it seems everyone is :( I can’t imagine using hundreds of dollars of tokens a day. But maybe this little tip for reviews might be helpful to someone.
smusamashah | a month ago
Brystephor | a month ago
I also have scripts to fetch specific database assets and forward them to slack channels so I can easily share them with a group rather than manually running a query and generating them.
I had a theory about improving a product. I asked it to build an offline simulation setup to try various implementations. The results were a bit fishy but i decided to give it a try and A/B testing is showing similar results.
And now im vibecoding a locally hosted dashboard. This one is less useful for anything specific, and more of a minor quality of life improvement, but its fun to just vibe code and see changes happen occasionally. Its not a critical thing.
viccis | a month ago
hakfoo | a month ago
Maybe that type of awkwardness is specific to my firm, but that's sort of what killed my drive to try to do that. We used to have one day every second week for that sort of work, but since it was scattered around, the tasks ended up disappearing-- nobody reviewed them and they didn't get merged.
So now they're trying to do a week-long internal hackathon to recover that vision, but I feel like that's going to produce a handful of big-bang ideas and not the 25 tiny tools that would actually streamline things.
mancerayder | a month ago
delecti | a month ago
ruraljuror | a month ago
chezelenkoooo | a month ago
Conscat | a month ago
harambae | a month ago
He clearly works at Apple, and they aren't laying people off.
nojs | a month ago
Are companies using per-token billing? Why - is there some reason they can’t buy the $200/mo Claude plan for every employee?
goosejuice | a month ago
LtWorf | a month ago
Staring with the fact that the whole industry is based on copyright infringement.
stavros | a month ago
novaleaf | a month ago
nl | a month ago
verdverm | a month ago
seanmcdirmid | a month ago
thinkingemote | a month ago
Does using AI increase or lower that failure rate?
Does seeing a project that uses AI fail mean it wasn't going to fail if it didn't use AI?
To try to answer it with my gut: I imagine that we could see more projects failing, but the percentage that fail would be the same. Most projects that use AI will fail because most projects generally will fail, but the time and cost to get a successful project will lower.
bob1029 | a month ago
I am watching a 10 person company try to run 3 different AI initiatives in parallel. Everyone wants to be "the guy" on this one. I cannot imagine there will ever be a bigger opportunity to ego trip as a technology person. This is it. This is the last call before it's all over. There are many businesses out there that are beyond traumatized by human developers taking them on bad rides. The microsecond they think this stuff will work they are going to fire everyone.
The psychosis comes from the tension here. We effectively have The Empire vs the rebel alliance now. I know how the movies go, but in real life I think I'd rather be working on the Death Star than anywhere else.
epolanski | a month ago
I cannot deny the impact of AI for my daily tasks at this point.
But I just don't enjoy the field anymore. With increased productivity, also coming from my stellar coworkers, it feels like we're rat racing who outputs more.
The quality is good, and having very strong rails at language and implementation level, strong hygiene, etc helps tremendously.
But reality is that the pace of product vastly outpaces the pace at which I can absorb it's changes (I'm also in a very complex business logic field), and the same might be true about my understanding of the systems which are changing too fast for me to keep up.
I feel mentally fatigued from a long time, I don't enjoy coding no more bar the occasional relaxing personal project where I can spend the time I want without pressures on architectural or implementation details.
I'm increasingly thinking of changing field, this one is dying right under our eyes.
I often read comments about HN users still delving at their place with technical details or rewriting AI code to their liking.
I'm increasingly sure that these people live in happy bubbles where this luxury still exists. But this methodology of work is disappearing across the industry, team by team.
Of course SE will not disappear over night, but the productivity expectations, the complexity ballooning are raising the bar where only incredibly skilled and productive engineers will be still able to practice SE properly, and as long as they meet stakeholders expectations or keep living in those bubbles.
kilroy123 | a month ago
I'm trying so hard to pivot away because of this.
choeger | a month ago
The question is: Will we live in the world of breathless re-implementation, new features every week, rebranding every quarter or will we eventually discover the value of stability, software that does its thing more or less optimally for decades?
Recent examples of things like curl or Firefox are interesting in that regard. Will we end up with a nearly perfect HTTP user agent and stick with it for decades?
ngruhn | a month ago
Sounds like we prefer stability for stuff we use but not for stuff we sell.
trwhite | a month ago
tossandthrow | a month ago
It seems like he is pointing out that Ai will increase the complexity of a system oblivion, and that this is the discussion that can not be had.
Bit I am more than happy to talk about how I am using Ai to reduce complexity and remove architectural debt that I otherwise could not justify spending time on.
skywhopper | a month ago
dkobia | a month ago
solatic | a month ago
Calling this "psychosis" is maybe a neologism but it's apt in perspective.
All that's actually new with "AI psychosis" is an acceleration of that phenomenon. The agents will summarize status faster than any middle manager. Claude will happily draw you any "up-and-to-the-right" graph you please, with the most common contemporary examples being "tokens burned" and "lines of code written". And vibe coding doesn't even require paying the cost of a mass layoff to get the "familiarity debt".
There have always been both good and bad engineering leaders. No tool will magically make a bad leader into a good leader overnight. There is nothing new under the sun.
lo_zamoyski | a month ago
Worth also noting is that while there is plenty to criticize about AI use — especially any cultish behavior surrounding it — plenty of naïveté about the quality of its results, there is a also a strain of categorical opposition to it among some tech people that is equally off and that has all the hallmarks of the chickens coming home to roost.
For years, many in tech gladly “automated away” all sorts of jobs. Large salaries were showered on them for doing so, or at least promising to do so (there was and is plenty of bullshit here, too). Now, AI appears to threaten to derail the tech gravy train, especially for SWE work that’s run-of-the-mill (which is most of it). Now automation is bad. It’s a delicious juxtaposition.
elif | a month ago
fjdjshsh | a month ago
Maybe the problem is you, but you won't figure that out if you think the other person has psychosis.
For example, maybe you need to do a better job explaining, changing your language, simplifying things, being more concrete with consequences.
Or maybe you aren't understanding that the other person has different objectives/ loss function that makes them make seemingly weird conclusions.
deadbabe | a month ago
sdeframond | a month ago
Rewriting in rust does makes things faster but if an algorithm is O(n²), the improvement won't take us much farther.
Similarly with AI, if complexity is not structurally adressed, the velocity gains are but temporary.
robofanatic | a month ago
Simon_O_Rourke | a month ago
Only by walking us into some revenue or customer impacting failure - through inappropriately having junior devs doing senior level things - will some sense of sanity start to prevail again.
popcorncowboy | a month ago
iamacyborg | a month ago
They're also reportedly now giving staff AI-related "homework" in an attempt to force staff to use AI more.
p2detar | a month ago
jqpabc123 | a month ago
Changing this focus is not easy but one thing that will usually do the trick is economic issues.
In other words; in order to get any serious consideration, something has to be broken.
AI is perfectly capable of doing this given enough time.
deadbabe | a month ago
rglover | a month ago
It's a tool; not the second coming.
hu3 | a month ago
Cars replaced horses.
But AI is poised to replace a large chunk of brain labour.
Where's the ceiling?
rglover | a month ago
A stable civilization that doesn't devalue human life and well-being to the point of absurdity.
sometimelurker | a month ago
> People just need to calm down
I think people need to make sure ceilings are built, and we can calm down once we're done.
sometimelurker | a month ago
rglover | a month ago
sometimelurker | a month ago
kalkin | a month ago
The stock market keeps going up in the face of the indefinite closure of Hormuz. We're investing in datacenters at a scale that only makes sense if AI capabilities continue to advance to the point where they surpass most humans at most white collar tasks, if not reach superintelligence.
And what are the possible outcomes?
- Bust. We've come away with a useful tool but the hundreds of billions of capital expenditure were thrown away on a pipe dream.
- Success! We're the dog that's caught the car. Then what? Currently the political debate is, to caricature only slightly, between "oh no the datacenters will use more water than golf courses" and "lol what are you going to do, regulate matrix multiplication?". How the hell are we going to cope with introducing a new intelligent species?
Either way, it sure seems like we're collectively operating more in the interests of the future AI than in the interests of humanity. What is this, if not a sort of psychosis?
jl6 | a month ago
In other words, BAU for the last few thousand years.
1dom | a month ago
notpachet | a month ago
edoceo | a month ago
big_youth | a month ago
Vosporos | a month ago
ARandomerDude | a month ago
y0eswddl | a month ago
yet balk at someone deciding to fight back in kind and on an exponentially smaller scale, comparatively speaking?
johnnyanmac | a month ago
tardedmeme | a month ago
deejaaymac | a month ago
rambojohnson | a month ago
bluefirebrand | a month ago
Otherwise humanity is over
thfuran | a month ago
thfuran | a month ago
TFNA | a month ago
jpiasetz | a month ago
Why wouldn’t it? The closure leads to price increases which leads to inflation which leads to non-dollar assets (ie stocks going up in value)
Second from a US perspective the strait matters the least it has since world war 2. If the price stays high a bunch of fracking will come back online.
rhubarbtree | a month ago
virgil_disgr4ce | a month ago
notpachet | a month ago
kermatt | a month ago
kalkin | a month ago
I think this argument proves too much. Historically energy shocks have led to recessions, and in recessions the stock market usually doesn't go up. And the US economy is certainly exposed to global recession regardless of whether we're a net exporter of fossil fuels.
ericmay | a month ago
The Strait of Hormuz is, basically not a big deal unless you're driving your big ole' truck. Americans are price sensitive and so some companies will have to absorb pricing increases, customers will absorb some others, and so forth. In other words, business as usual. Of course the closure of the Strait is a big problem for most of the rest of the world. They better get on with figuring out how to get Iran to stop being so chaotic in the region or we'll just keep it shut down indefinitely. No big deal.
Because the United States has so many advantages (primary global reserve currency, robust and efficient capital markets, highly sophisticated and dynamic economy across all sectors except luxury goods, &c.) it's able to weather these storms much easier than most other countries. As a country that also imports so much, if we spend less on imported products that's less of a problem than not being able to sell products. A recession isn't great, but the current parameters seem to suggest to me it's less of a problem for the United States - perhaps why we're in part seeing stock market valuations continue to climb.
thfuran | a month ago
Are you serious? Even ignoring the other things that ship through there, a significant disruption to global energy supply is significant to most people. If you're not driving a truck, you're probably using goods that contain plastic or took energy to produce or were moved from one place to another in fuel-powered vehicles. If, somehow, you're not, you're probably using services that are.
macintux | a month ago
ericmay | a month ago
The world let this disease (IRGC) fester in the region for too long, and now because of that the fix is going to require significant pain. The IRGC in its current form has run its course and will not be allowed to threaten American interests, allied interests (whether that's Israel, UAE, Saudi Arabia, or otherwise), and they will not be permitted to build a nuclear weapon or threaten global trade.
sofixa | a month ago
The reason nobody was dumb enough to attack them before is that it's an unwinnable conflict. They don't need a lot to close the Strait of Hormuz, a few guys rolling mines off a beach would do that. And they have a lot more, like missiles and drones to do damage at a distance too.
And it's a regime that has at least a million loyal fanatics ready to fight for it (the Basij, the org that did unarmed meat waves against Iraq to defend the regime). So any invasion is an absurd proposition.
So what, the hope is that the theocratic kleptocracy will give up? Not even a child could be so naive. They literally believe in martyrdom, whacking a few of the top dogs means nothing.
It's like the Kims, nobody can unseat them. Only this is far worse, because Iran has the leverage of Hormuz, and it knows it can wait - because they don't care about the people - while the US and global economy suffer until they fold. Especially with midterm elections coming, the US will fold.
ericmay | a month ago
> Especially with midterm elections coming, the US will fold.
These are the kinds of misunderstandings that are disappointing to see. There is no disagreement here amongst the political class. It is political theater for votes. Apparently you’re susceptible to the marketing.
We don’t need to invade Iran. We just keep the Strait closed since we control it and then Iran’s economy simply fails and the worst thing that happens for America is higher prices. But we can handle that.
sofixa | a month ago
The political class answers, in a way, to the population. The American population is extremely sensitive to the price they get at the gas station (because of the complete lack of alternatives in driving in most places, and the average car having bad fuel economy). If by election time the prices are the same, the ruling party will get punished. And the ruling party doesn't want that.
PygmySurfer | a month ago
majormajor | a month ago
What's your sales pitch exactly for how that's the best thing for the non-US rest-of-the-world? What's the US's post-WWII track record, success-wise, in regime-change foreign wars, how much would you trust the US on this one?
ericmay | a month ago
> What's your sales pitch exactly for how that's the best thing for the non-US rest-of-the-world? What's the US's post-WWII track record, success-wise, in regime-change foreign wars, how much would you trust the US on this one?
Honestly not all that bad for the US.
Korea - we stopped the North Koreans from taking over the entire peninsula. It’s China and Russia’s fault that the hell hole we know as North Korea exists today.
Vietnam - unnecessary war, but we won the peace.
Panama - took out Noriega
Desert Storm - stopped Saddam and kicked his thugs out of Iraq.
Serbia and Bosnia - NATO campaign. I’m personally a little unsure if the results were good or not but I understand we collectively stopped a genocide.
Afghanistan - we tried our best and made some mistakes along the way. Eventually got Bin Laden though. Too bad the rest of the world didn’t help. Now we’re seeing a massive regression in women’s rights there.
Iraq - probably not worth the money, but Iraq went from a brutal dictatorship under Saddam to a much more stable and peaceful country with a Parliament.
Venezuela - Took out Maduro with no losses.
Iran - TBD on the long term but we’ve stopped the IRGC buildup and at least bought time to figure out what to do.
The rest of the world stands on the sidelines and complains and complains yet the United States actually has the balls and will to do things. We aren’t perfect, but without US military action or at least the threat the world would be much more dangerous and much worse off. China sure as hell isn’t going to send troops to liberate Kuwait. Europe doesn’t have the military capability to stop Iran from getting nuclear weapons and exerting a stranglehold on a large chunk of global oil supply.
toraway | a month ago
ericmay | a month ago
Are you unfamiliar with the term? In the case of Vietnam we “lost” the war, yet today we have pretty strong and good relations with Vietnam. Hence we won the peace.
> Why are you lying about this?
I have a different perspective, but that doesn’t mean I’m lying.
Of course many countries contributed in various ways to Afghanistan, and as a former member of US military I have incredible respect for our friends and allies and still do today. But at the end of the day the vast majority of the manpower, cost, and equipment was American and the country could not be won solely on military power alone and needed much more support diplomatically, politically, economically, and in terms of aid.
The other problem with your argument is if you claim that Afghanistan was an American failure it contradicts your assertion and instead everyone failed, except that the US contributed the most. You can’t have it both ways.
hdgvhicv | a month ago
ericmay | a month ago
Some Americans need to have their understanding of the world checked. If you think high gas prices are the end of the world, just wait until we have a real problem. Are we going to be incapable of fighting a war because Netflix and Pepsi prices went up or it's too expensive to coal roll down the highway?
Separately as someone who supports both Ukraine and the US and taking down the Iranians it's amusing to see each political tribe get mad about gas prices as it is convenient for them. When Russia invaded Ukraine, MAGA was screaming from the rooftops and putting Joe Biden "I did that" stickers on gas pumps. Now that we're taking on the Iranians all of the commies are doing the same thing (aren't gas prices good anyway since we need to do something about global warming?). Neither side of populist is worthy of serious consideration. Stay the course, whether that's supporting high gas prices because of Russia or because of Iran.
GIFtheory | a month ago
ericmay | a month ago
Cuba ran out of fuel because we took out their thug partner in Maduro. If they wanted to drop the whole authoritarian communist dictatorship stuff and their involvement in the disaster that became Venezuela and partnering with the Russians then they'll be better off.
tardedmeme | a month ago
Since when is it acceptable to invade another country just for being communist or a dictatorship? Conventionally it's up to the people in those countries to overthrow a dictator. Other countries only get involved if the dictator attacks them (like the USA dictator did).
ErroneousBosh | a month ago
Do you like being able to buy food?
ericmay | a month ago
thfuran | a month ago
Food production will decrease, and even moderate increases in food prices mean many people unable to afford enough food.
ericmay | a month ago
incanus77 | a month ago
thephyber | a month ago
Worst take I’ve ever seen on this website.
> Americans are price sensitive and so some companies will have to absorb pricing increases, customers will absorb some others, and so forth. In other words, business as usual.
No. Not all goods/services have the same price elasticity. At some point, people stop buying some goods if they are too expensive. They stop commuting to work. We start to see breakdown of the supply chain.
Literally 100% of many towns in the US depend on trucks to deliver food to their grocery stores and the inventory on hand usually only lasts a few days. Once those trucking deliveries become unaffordable for either party in the contract, society starts to. Real down.
Consumers don’t magically make more money when the price of gas rises. It starts to crowd out their ability to spend on other things. The poorest of the working class likely has to commute the furthest so they will end up sacrificing something to keep paying for the commute - food or rent or utilities.
The US doesn’t weather this because we have “a sophisticated supply chain”. _If_ we weather it, it’s because we created the US SPR after the last major oil crisis and we have significant domestic supply (although not all oil is fungible so we might not have enough light sweet to keep the economy running at 100%).
ericmay | a month ago
The second problem with your argument is that you’re using it as an argument against the war but it’s actually an argument in favor of the war. Why is that? Because as Iran continues to load up on missiles and pursue a nuclear weapon they reach a point where they can assert control over the Strait and shut down shipping pending tribute to their theocracy (maybe if it was a Christian one you’d have a bigger problem with it? Idk?) and then we couldn’t do anything about it. The world isn’t static. Stop treating it as such.
jpiasetz | a month ago
thephyber | a month ago
Also, the US SPR was created in 1975, so we are going to get to see if it actually works to absorb an oil shock like this.
Most likely there will be some places which are almost unaffected while others are going to see unaffordable price spikes (more than 400%). The pain won’t be spread evenly.
rf15 | a month ago
ori_b | a month ago
People say that LLMs won't take us there. I think that's accurate, but there's a great deal of research going towards the next breakthroughs. How much are you willing to bet that all future attempts will fail?
We're trying very hard to build an ugly future.
Miner49er | a month ago
AbioticAdam | a month ago
Miner49er | a month ago
Faaak | a month ago
redleader55 | a month ago
dawnerd | a month ago
pigpop | a month ago
ufish235 | a month ago
Muromec | a month ago
warumdarum | a month ago
dmoy | a month ago
Muromec | a month ago
ludwik | a month ago
Muromec | a month ago
tardedmeme | a month ago
Muromec | a month ago
code_biologist | a month ago
All to say, your SO's dad would have been right at any point prior to the current financial cycle. Knowing what's changed doesn't make forecasting easier though.
kalkin | a month ago
But also, even if bust is business as usual in the big picture and not a social disaster long term, it's of course not what individual investors want for their particular current investments.
slumberlust | a month ago
chatmasta | a month ago
uncivilized | a month ago
dheera | a month ago
Why wouldn't it? The value of the USD is decreasing, the value of the companies to the world stays the same => stock price in USD increases.
The real thing to analyze is "amount of VOO shares you need to buy a Chipotle meal / Uber ride / 1 month's rent in SF / etc."
Miner49er | a month ago
root_axis | a month ago
Miner49er | a month ago
CorrectHorseBat | a month ago
ansgri | a month ago
whateveracct | a month ago
heh this is the trick. The tech companies will angle for a bailout and they'll benefit from all this speculative data center building. Compute is generally useful.
abracadaniel | a month ago
whateveracct | a month ago
akomtu | a month ago
IMO, what's happened is a few richest investors in the world had access to the uncensored tier of AI, talked to it and came out with impression that they've witnessed something so dark, so much beyond anything we can imagine, that the only course forward is towards the transcendent abyss. Call it AI psychosis or demonic inspiration, but they are the people who control the economy, so they are dragging everyone with them. "Operating in the interest of the future AI" is a neat way to put it.
bitexploder | a month ago
neuroelectron | a month ago
[plausible sounding nonsense]
zzzeek | a month ago
Never overestimate the billionaire class....
regularization | a month ago
If there is a psychosis, what is it? It is not an AI psychosis - modern AI started in the 1940s, or by some definitions before, and made progress up until 15 years ago to where deep neural networks became viable. And it has been progress on every front since then. No psychosis, it is doing well.
You mention the stock market, and that is another story. Cryptocurrencies, sub-prime loans, dot-com crash, Asian financial crisis. The economy has veered from crisis to crisis, overproduction and overproduction to crashes and bailouts.
AI is doing just fine - the past 15 years are a success for it we did not see in the decades before. If the economy as constituted is dealing with this in a "psychotic" fashion, it would not be the first time.
warumdarum | a month ago
zombot | a month ago
dismalaf | a month ago
sbochins | a month ago
wnmurphy | a month ago
Also $1T in data center investment makes sense when you realize that companies are racing to create virtual white collar workers. Google spends $9B a year on software engineers.
sofixa | a month ago
Which will take decades to become addressable. Self-driving cars work OK in a few cities in one country. Expanding that to be able to cover Mumbai and Omsk and Nairobi will require significantly more work.
> Also $1T in data center investment makes sense when you realize that companies are racing to create virtual white collar workers.
Does it make sense? How much would the resulting virtual white collar worker cost? Because datacenters have running operational costs, and so do the people operating them and working on the software that runs in them.
lumost | a month ago
The money printer will be used, and maybe it all works out - or we see wealth hyperinflation and build out our own aristocracy.
PieTime | a month ago
MichaelZuo | a month ago
Hundreds of billions are changing hands globally, every week, at the retail level alone.
And that happens literally every week, week after week.
That constitutes a massive market in any sense I can think of.
tardedmeme | a month ago
MichaelZuo | a month ago
That needs a way more complex explanation than simple gut feeling.
charlysl | a month ago
Henry Ford II: "Walter, how are you going to get those robots to pay your union dues?" Walter Reuther: "Henry, how are you going to get them to buy your cars?"
irishcoffee | a month ago
jimkleiber | a month ago
And for so long, I've had people tell me to just get a job. But I tell them that I don't want a job: I want money and I want something to do. Those two things don't have to be together.
I think this is the hard part: philosophically so many of us have learned we need jobs and don't realize a job can be decomposed into money and something to do.
So I think we need to start looking more creatively at 1) how people receive money from others and 2) how people give services to others.
irishcoffee | a month ago
Nobody cares that you want money and you want something to do that you enjoy. Nobody ever will.
If you actually dig into all the social programs that exist at least in the US, they’re just a massive payday for a small group of people under the guise of bettering humanity.
College/education is a fantastic example. Education as it has been established today is a joke. The humanities were originally established for rich bored wives to have something to do. They were never meant to create value. Colleges hang anvils around the necks of naive children via loans telling them “yes if you major in history you’ll have a job!” This is a joke, and a bad one.
Huxley was on to something. If everyone is educated, nobody collects trash, or chops lumber, mines minerals and metals, etc. it’s a big fucking not-talked-about open secret.
Nobody cares, either you bring something to the table someone else can exploit for money, or you lean into “I’m helpless and the government owes it to me to take care of me because I’ve been indoctrinated into learned helplessness.”
“AI” will at best lead to anarchy at this point, if all the grand visions of the billionaires comes to fruition. People have already tried to kill sama and burn his house down. Wait until armed humvees are driving around data centers. It’s coming.
jimkleiber | a month ago
So when we talk of people doing labor for money, we are assuming they can only own their body and receive money from that?
irishcoffee | a month ago
jimkleiber | a month ago
You paint the economic model as a false dichotomy, and the main point of my posting was that it is not a false dichotomy. It is not either have a job (and be exploited by someone else) or be helpless and rely on government handouts.
For example, what if people who got laid off from companies were given significant stock in the company, so that they might partake in the potential savings and gains from replacing the workers with AI or other tools?
The whole conversation seemed to be about the economic model, so I'm not sure how it is a distraction, a boogeyman, or inconsequential.
irishcoffee | a month ago
You have described less than 0.1% of the US population, not to mention the rest of the world.
I get it, you have an idea in your head and you're struggling to see past it. Read Brave New World.
jimkleiber | a month ago
Fair, my one example on layoffs may not land with you.
But do you want us to just sink into the helplessness of us all being screwed or do you want to try to find solutions that might allow us to feel some sense of agency and hope?
34df | a month ago
you may not like the fact the fat capital owner may not be lifting a finger, but they certaintly aren't getting a free lunch.
jimkleiber | a month ago
So I don't think it's a free lunch, it's more risk-for-lunch than labor-for-lunch. Maybe you could argue laborers are still risking their body or something, but I think the point might stand.
captainbland | a month ago
nine_k | a month ago
OTOH replacing people with AI would indeed bring about a huge economic downturn. What would be good is augmenting humans so that they can do 10x more. That would enable things that are hard to imagine exactly now, much like computers enabled interesting transformations in the society from 1980s to 2010s.
The current crop of AI is by construction unable to reach the human level of cognition, but it is quite good at doing some symbolic manipulation tasks. We will get used to that, and will integrate that in our workflows. Humans are still going to be needed.
bobthepanda | a month ago
alluro2 | a month ago
majormajor | a month ago
That's not a new market, that's a new feature in an existing market. Lots going on in transportation and I'm not seeing any scenario where self-driving cars vastly increase total output vs just eat up other forms of transportation and change where people live/how long they commute.
> Also $1T in data center investment makes sense when you realize that companies are racing to create virtual white collar workers. Google spends $9B a year on software engineers.
Similarly, many companies are trying to be more efficient - "do what we already do, but better". That's different than growth.
What could Google do with 9B on software agents? Let's say the future of them is amazing and this means they could write 100x more code than they can today.
Has Google recently showed much ability to turn "more/faster code" into "superbly profitable new market"?
Someone's gonna have to crack the demand side issue for anything transformative to happen.
victoro | a month ago
Well they are projected to spend $175 - $185B on capex in this year alone most of it for AI buildout. Lets say only 150B of that is for AI. If they can then somehow replace all their software engineers with AI that they then run for free and depreciate over 10 years then they just replaced 9B a year software expense with 15B a year depreciation expense for the next decade. Yes this is grossly oversimplified but it still illustrates how crazy high of a bet they're making on AI.
nearbuy | a month ago
ericbarrett | a month ago
I believe the One Big Beautiful Bill Act allows full depreciation in the first year: https://www.bassets.net/blog/obbba-depreciation-2025-2026-gu...
dahinds | a month ago
ericbarrett | a month ago
phs318u | a month ago
No. It doesn’t. And if you’re defining “drives” as “it drives as well as I do” then you probably shouldn’t be on the road.
> makes sense
Nothing about any of this makes sense. Tell me, when all white collar jobs are replaced by AI, where will the customers come from? Who will have income to afford your products or services? The poor barista whose surveillance videos are training the robot that will soon replace them?
Leaving aside any consideration of human compassion or questioning of the purpose of an economic system (hint: it’s not just an abstract machine), shrinking the pool of potential customers by orders of magnitude has never been a recipe for sustainable success (let alone growth).
somewhatgoated | a month ago
827a | a month ago
0x3f | a month ago
Such as?
SOLAR_FIELDS | a month ago
hmokiguess | a month ago
The energy feels misdirected and maybe also a communication issue, I think spreading awareness needs to come not from attacking and also not from attempts to change people’s perception. It’s also quite challenging to distill a concept when it’s new, we learn both from our experiences and experiences of others; but, so far, these alleged systems that will eventually collapse, haven’t done so yet and it makes it sound like you’re preaching and predicting, condemning even, rather than raising awareness and education.
Not trying to sound hopelessly optimistic either, just that the other extreme isn’t also helpful, and that a spectrum is not what we want it to be but what the collective shapes it, so saying psychosis is rejecting the harsh reality that they’re far removed from your worldview and not working towards an understanding.
EDIT: Maybe I'm old and I don't get twitter, I also don't know much about the challenges he faced communicating his concerns, I sort of had a meta comment with the intent of "try listening more first, some people are difficult to reason with but respond better if you just let them speak and look for a teachable moment during the conversation". Anyways, I'm in agreement that there's too much unsupervised AI in the wild, I'm not saying he's wrong more like saying that doubling down on "stop doing that" will likely be ignored by those that are already ignorant to it, hence what I wrote above.
gofreddygo | a month ago
He is clear in pointing out the hard earned lessons we have learned before and how the current actions are essentially undermining it. This is dumb (i agree) and he expects better from people whom he respects.
it's clear, personal, logical. I don't understand what your criticism is.
hmokiguess | a month ago
vlovich123 | a month ago
zemo | a month ago
hmokiguess | a month ago
zombot | a month ago
https://news.ycombinator.com/item?id=48148337
ttz | a month ago
bsoles | a month ago
ryanSrich | a month ago
apassintofuture | a month ago
low_tech_love | a month ago
blazespin | a month ago
What we need is automated research that leads to real results. This is possible, but it has yet to prove out. I am concerned that unless the AI companies focus entirely on this, it may be a while before we actually see true benefits from this.
What's worse, is there is an urgent and desperate need for automated research, as we have been seeing diminishing returns in human produced research for some time now: https://web.stanford.edu/~chadj/IdeaPF.pdf
rogermarley | a month ago
It sometimes feels like AI chatbot use is like the doomscrolling of work - it's always easier just to dump something into the chatbot than think about it.
The real question is: what's the fallout going to be after the dust settles? My guess is that the explosion of codebase entropy now underway from this is going to make for an interesting future - once it reaches the point where AI agents are spinning constantly despite progress grinding to a halt.
And they're be no veterans who know the codebase deeply to step in and fix things because it was all vibecoded - and then what are companies going to do?
I think that's the point where they turn back to the thinkers for help.
kshri24 | a month ago
thenthenthen | a month ago
Khaine | a month ago
Everyone has become like petulant children. Senior leaders want access to every shiny tool (CoWork/Codex/etc) that has some buzz around it. No one seems to care about the cost or whether we are actually realising benefits.
It's sheer madness, and you can't push back. I think AI can significantly help people be more productive, and I can see a future where they safely take on more autonomy. But we are far from that world.
ileonichwiesz | a month ago
And I found it really funny, because for what? Use it for what? It’s a tool. Imagine a guy coming down to a construction site where everything is progressing fine and saying “We need to use more screwdrivers”.
j45 | a month ago