I don't think LLMs are the right tool for pattern enforcement in general, better to get them to create custom lint rules.
Agents are pretty good at suggesting ways to improve a piece of code though, if you get a bunch of agents to wear different hats and debate improvements to a piece of software it can produce some very useful insights.
I feel like pricing needs to be included here. I kind of don't care about 10 percentage points if the cost is dramatically higher. Cursor Bugbot is about the same cost but gives 10x the monthly quota of Qodo.
I know this is focused solely on performance, but cost is a major factor here.
> We believe that code review is not a narrow task; it encompasses many distinct responsibilities that happen at once. [...]
> Qodo 2.0 addresses this with a multi-agent expert review architecture. Instead of treating code review as a single, broad task, Qodo breaks it into focused responsibilities handled by specialized agents. Each agent is optimized for a specific type of analysis and operates with its own dedicated context, rather than competing for attention in a single pass. This allows Qodo to go deeper in each area without slowing reviews down.
> To keep feedback focused, Qodo includes a judge agent that evaluates findings across agents. The judge agent resolves conflicts, removes duplicates, and filters out low-signal results. Only issues that meet a high confidence and relevance threshold make it into the final review.
> Qodo’s agentic PR review extends context beyond the codebase by incorporating pull request history as a first-class signal.
I'm building a benchmark for coding agent memory following your philosophy. There are so many memory tools out there but I have not been able to find a reliable benchmark for coding agent memory. So I'm just building it myself.
A lot of this stuff is really new, and we will need to find ways to standardize, but it will take time and consensus.
It took 4 years after the release of the automobile to coin the term milage to refer to miles driven per unit of gasoline. We will in due time create the same metrics for AI.
Some feedback for the team, looked at pricing page and saw it more expensive ($30/dev/mo) and highly limiting (20prs per month per user). We have devs putting up that many prs in a single day. With this kind of plan pretty much no way we would even try this product
I'm trying to bring a slightly different take to the pricing of ShipItAI (https://shipitai.dev, brazen plug). I've got a $5/mo/active dev + Bring Your Own Key option for those that want better price controls.
Still early in development and has a much simpler goal, but I like simple things that work well.
For the first, your signal would be weak, for those events are rare. I don't think deleting and reverting is a signal of quality. Rather, it demonstrates bad changes, as you said. This does not tell the model what good code is, just what it is not.
I'd be interested, but they don't even list any anthropic model on their code review benchmark, so I feel like they haven't really tested their benchmark on SOTA models.
Whenever I see this, I make the (almost always correct) assumption that the SOTA models had an advantage, with the alternative explanation being a complete lack of awareness of the state of AI (which is very very rare for a tool like this).
With SOTA missing, it also is a strong indicator that someone like you is not the target audience.
CuriouslyC | a day ago
Agents are pretty good at suggesting ways to improve a piece of code though, if you get a bunch of agents to wear different hats and debate improvements to a piece of software it can produce some very useful insights.
mbesto | a day ago
Nope, no mention of how they do anything to alleviate overfitting. These benchmarks are getting tiresome.
polynomial | 19 hours ago
aetherspawn | a day ago
zamadatix | a day ago
mdeeks | a day ago
I know this is focused solely on performance, but cost is a major factor here.
falloutx | 23 hours ago
Story as old as time.
shimman | 22 hours ago
andai | 20 hours ago
>thing gets optimized
falloutx | 12 hours ago
kachapopopow | 23 hours ago
esafak | 23 hours ago
Apparently this is in support of their 2.0 release: https://www.qodo.ai/blog/introducing-qodo-2-0-agentic-code-r...
> We believe that code review is not a narrow task; it encompasses many distinct responsibilities that happen at once. [...]
> Qodo 2.0 addresses this with a multi-agent expert review architecture. Instead of treating code review as a single, broad task, Qodo breaks it into focused responsibilities handled by specialized agents. Each agent is optimized for a specific type of analysis and operates with its own dedicated context, rather than competing for attention in a single pass. This allows Qodo to go deeper in each area without slowing reviews down.
> To keep feedback focused, Qodo includes a judge agent that evaluates findings across agents. The judge agent resolves conflicts, removes duplicates, and filters out low-signal results. Only issues that meet a high confidence and relevance threshold make it into the final review.
> Qodo’s agentic PR review extends context beyond the codebase by incorporating pull request history as a first-class signal.
thierrydamiba | 22 hours ago
A lot of this stuff is really new, and we will need to find ways to standardize, but it will take time and consensus.
It took 4 years after the release of the automobile to coin the term milage to refer to miles driven per unit of gasoline. We will in due time create the same metrics for AI.
seg_lol | 14 hours ago
logicx24 | 23 hours ago
mattvv | 23 hours ago
esafak | 23 hours ago
DerArzt | 8 hours ago
zhubert | 22 hours ago
Still early in development and has a much simpler goal, but I like simple things that work well.
freakynit | 15 hours ago
mohsen1 | 20 hours ago
Merged PRs being considered good code?
esafak | 19 hours ago
mohsen1 | 9 hours ago
- vX.X.1 releases. when software was considered perfect but author had to write a fast follow up fix. very real bugs with real fixes
- Reverts. I'm sure anyone doing AI code review pays attention to this already. This is a sign of bad changes, but as important.
- PRs that delete a lot of code. A good change is often deleting code and making things simpler
esafak | 6 hours ago
steve_avery | 18 hours ago
nomel | 18 hours ago
With SOTA missing, it also is a strong indicator that someone like you is not the target audience.