1. I absolutely agree there's a bubble. Everybody is shipping a code review agent.
2. What on earth is this defense of their product? I could see so many arguments for why their code reviewer is the best, and this contains none of them.
More broadly, though, if you've gotten to the point where you're relying on AI code review to catch bugs, you've lost the plot.
The point of a PR is to share knowledge and to catch structural gaps. Bug-finding is a bonus. Catching bugs, automated self-review, structuring your code to be sensible: that's _your_ job. Write the code to be as sensible as possible, either by yourself or with an AI. Get the review because you work on a team, not in a vacuum.
None of these tools perform particularly well and all lack context to actually provide a meaningful review beyond what a linter would find, IMO. The SOTA isn't capable of using a code diff as a jumping off point.
Also the system prompts for some of them are kinda funny in a hopelessly naive aspirational way. We should all aspire to live and breathe the code review system prompt on a daily basis.
I don't know that I fully agree with that. I use Copilot for AI code review - just because it's built in to GitHub and it's easy - and I'd say results are variable, but overall decent.
Like anything else AI you need to understand what you're doing, so you need to understand your code and the structure of your application or service or whatever because there are times it will say something that's just completely wide of the mark, or even the polar opposite of what's actually the case. And so you just ignore the crap and close the conversation in those situations.
At the same time, it does catch a lot of bugs and problems that fall into classes where more traditional linters really miss the mark. It can help fill holes in automated testing, spot security issues, etc., and it'll raise PRs for fixes that are generally decent. Sometimes not but, again, in these cases you just close them and move on.
I'd certainly say that an AI code review is better than no code review at all, so it's good for a startup where you might be the only developer or where there are only one or two of you and you don't cross over that much.
But the point I actually wanted to get to is this: I use Copilot because it's available as part of my GitHub subscription. Is it the best? I don't know. Does it add value with zero integration cost to me? Yes. And that, I suspect, is going to make it the default AI code review option for many GitHub subscribers.
That does leave me wondering how much of a future there is for AI code review as a product or service outside of the hosting platforms like GitHub and Gitlab, and I have to imagine that an absolutely savage consolidation is coming.
I installed CodeRabbit for our reviews in GitLab and am pretty happy with the results, especially considering the low price ($15/user/mo I think).
It regularly finds problems, including subtle but important problems that human reviewers struggle to find. And it can make pretty good suggestions for fixes.
It also regularly complains about things that are possible in theory but impossible in practice, so we've gotten used to just resolving those comments without any action. Maybe if we used types more effectively it would do that less.
We pay a lot more attention to what CodeRabbit says than what DeepSource said when use used it.
AI code review to me is similar to AI code itself. It's good (and constantly getting better) at dealing with mundane things, like - is the list reversed correctly? Are you dealing with pointers correctly? Do you have off by 1 issues?
Where they suck is high level problems like - is the code actually solving the business problem? Is it using right dependencies? Does it fit into broader design?
Which is expected for me and great help. I'm more happy as a human to spend less time checking if you're managing lifecycle of the pointer correctly and focus on ensuring that code is there to do what it needs to do.
They 100% catch bugs in code I work on. Is it replacing human review fully? No, not yet. But it is a useful tool. Just like most of us wouldn’t do a code review without having tests, linters etc run first.
I suspect this is primarily a unit economics problem. To get context beyond the diff you really need the full repository or a robust AST, but the token costs to load that state for every PR make the margins impossible right now.
I liked that the post is self-aware that it's promoting its own product. But the writing seemed more focus on the philosophy behind code reviews and the impact of AI, and less on the mechanics of how greptile differs from competitors. I was hoping to see more on the latter.
Problem with Code Review is it is quite straightforward to just prompt it, and the frontier models, whether Opus or GPT5.2Codex do a great job at code-reviews. I don't need second subscription or API call when the first one i already have and focus on integration works well out of the box.
In our case, agentastic.dev, we just baked the code-review right into our IDE. It just packages the diff for the agent, with some prompt, and sends it out to different agent choice (whether claude, codex) in parallel. The reason our users like it so much is because they don't need to pay extra for code-review anymore. Hard to beat free add-on, and cherry on top is you don't need to read a freaking poems.
we use codex review. it's working really well for us.
but i don't agree that it's straightforward. moving the number of bugs catched and signal to noise ratio a few percentage points is a compounding advantage.
it's a valuable problem to solve, amplified by the fact that ai coding produces much more code.
that being said, i think it's damn hard to compete with openai or anthropic directly on a core product offering in the long run. they know that it's an important problem and will invest accordingly.
Contrary to some of the other anecdotes in this thread, I've found automated code review to discover some tricky stuff that humans missed. We use https://www.cubic.dev/
This article has a catchy headline, but there's really no content to it. This is content marketing without content. It seems like every week on Hacker News, there's a dozen of these. All seemingly code reviewers, too. Keep it to LinkedIn.
It's not terribly hard to write a Copilot GHA that does this yourself for your specific teams needs. Not sure why you'd been to bring a vendor on for this....
What do the vendors provide?
I looked at a couple which were pretty snazzy at first glance, but now that I know more about how copilot agents work and such, I'm pretty sure in a few hours, I could have the foundation for my team to build on that would take care of a lot of our PR review needs....
> Only once would you have X write a PR, then have X approve and merge it to realize the absurdity of what you just did.
I get the idea. I'll still throw out that having a single X go through the full workflow could still be useful in that there's an audit log, undo features (reverting a PR), notifications what have you. It's not equivalent to "human writes ticket, code deployed live" for that reason
>A human rubber-stamping code being validated by a super intelligent machine is the equivalent of a human sitting silently in the driver's seat of a self-driving car, "supervising".
So, absolutely necessary and essential?
In order to get the machine out of trouble when the unavoidable strange situation happens that didn't appear during training, and requires some judgement based on ethics or logical reasoning. For that case, you need a human in charge.
Good code reviews are part of team's culture and it's hard to just patch it with an agent. With millions of tools it will be arms race between which one is louder about as many things as possible because:
- it will have higher chance at convincing the author that the issue was important by throwing more darts - something that a human wouldn't do because it takes real mental effort to go through an authentic review,
- it will sometimes find real big issue which reinforces the bias that it's useful
- there will always be tendency towards more feedback (not higher quality) because if it's too silent, is it even doing anything?
So I believe it will just add more round of back and forth of prompting between more people, but not sure if net positive
Plus PRs are a good reality check if your code makes sense, when another person reviews it. A final safeguard before maintainability miss, or a disaster waiting to be deployed.
My company just finished a several week review period of Greptile. Devs were split over the usefulness of the tool (compared to our current solution, Cursor). While Greptile did occasionally offer better insights than Cursor, it also exhibited strange behavior such as entirely overwriting PR descriptions with its own text and occasionally arguing with itself in the comments. In the end we decided to NOT purchase Greptile as there were enough "not quite there" issues that made it more trouble than worthwhile. I am certain, though, that the Greptile team will resolve all those problems and I wish them the best of luck!
Reminder that this comes from from the founder that got rightly lambasted for his comments about work life balance and then doubled down when called out.
Maybe I'm buying into the cool-aid, but I actually really liked the self-aware tone of this post.
> Based on our benchmarks, we are uniquely good at catching bugs. However, if all company blogs are to be trusted, this is something we have in common with every other AI code review product. One just has to try a few, and pick the one that feels the best.
I've also noticed this explosion of code review tools and felt that there's some misplaced focus going on for companies.
Two that stood out to me are Sentry and Vercel. Both have released code review tools recently and both feel misplaced. I can definitely see why they thought they could expand with that type of product offering but I just don't see a benefit over their competition. We have GH copilot natively available on all our PRs, it does a great job, integrates very well with the PR comment system, and is cheap (free with our current usage patterns). GH and other source control services are well placed to have first-class code review functionality baked into their PR tooling.
It's not really clear to me what Sentry/Vercel are offering beyond what copilot does and in my brief testing of them didn't see noticeable difference in quality or DX. Feels like they're fighting an uphill battle from day one with the product choice and are ultimately limited on DX by how deeply GH and other source control service allow them to integrate.
What I would love to see from Vercel, which they feel very well placed to offer, is AI powered QA. They already control the preview environments being deployed to for each PR, they have a feedback system in place with their Vercel toolbar comments, so they "just" need to tie those together with an agentic QA system. A much loftier goal of course but a differentiator and something I'm sure a lot of teams would pay top dollar for if it works well.
No shit. What is the point of using an llm model to review code produced by an llm model?
Code review pressupose a different perspective, which no platform can offer at the moment because they are just as sophisticated as the model they wrap.
Claude generated the code, and Claude was asked if the code was good enough, and now you want to be in the middle to ask Claude again but with more emphasis, I guess?
If I want more emphasis I can ask Claude myself. Or Qwen.
I can't even begin to understand this rationale.
We used Greptile where I work and it was so bad we decided to switch to Claude. And even Claude isn’t nearly as good at reviewing as an experienced programmer with domain knowledge.
Why not let AI write the code and then have it reviewed by humans? If you use AI to review my code, then you can't stop me from using another AI to refute it: this only foreshadows the beginning of internal friction.
83 comments
[ 2.0 ms ] story [ 1273 ms ] thread> Independence
Any "agent" running against code review instead of code generation is "independent"?
> Autonomy
Most other code review tools can also be automated and integrated.
> Loops
You can also ping other code review tools for more reviews...
I feel like this article actually works against you by presenting the problem and inadequately solving them.
2. What on earth is this defense of their product? I could see so many arguments for why their code reviewer is the best, and this contains none of them.
More broadly, though, if you've gotten to the point where you're relying on AI code review to catch bugs, you've lost the plot.
The point of a PR is to share knowledge and to catch structural gaps. Bug-finding is a bonus. Catching bugs, automated self-review, structuring your code to be sensible: that's _your_ job. Write the code to be as sensible as possible, either by yourself or with an AI. Get the review because you work on a team, not in a vacuum.
Also the system prompts for some of them are kinda funny in a hopelessly naive aspirational way. We should all aspire to live and breathe the code review system prompt on a daily basis.
Like anything else AI you need to understand what you're doing, so you need to understand your code and the structure of your application or service or whatever because there are times it will say something that's just completely wide of the mark, or even the polar opposite of what's actually the case. And so you just ignore the crap and close the conversation in those situations.
At the same time, it does catch a lot of bugs and problems that fall into classes where more traditional linters really miss the mark. It can help fill holes in automated testing, spot security issues, etc., and it'll raise PRs for fixes that are generally decent. Sometimes not but, again, in these cases you just close them and move on.
I'd certainly say that an AI code review is better than no code review at all, so it's good for a startup where you might be the only developer or where there are only one or two of you and you don't cross over that much.
But the point I actually wanted to get to is this: I use Copilot because it's available as part of my GitHub subscription. Is it the best? I don't know. Does it add value with zero integration cost to me? Yes. And that, I suspect, is going to make it the default AI code review option for many GitHub subscribers.
That does leave me wondering how much of a future there is for AI code review as a product or service outside of the hosting platforms like GitHub and Gitlab, and I have to imagine that an absolutely savage consolidation is coming.
It regularly finds problems, including subtle but important problems that human reviewers struggle to find. And it can make pretty good suggestions for fixes.
It also regularly complains about things that are possible in theory but impossible in practice, so we've gotten used to just resolving those comments without any action. Maybe if we used types more effectively it would do that less.
We pay a lot more attention to what CodeRabbit says than what DeepSource said when use used it.
Where they suck is high level problems like - is the code actually solving the business problem? Is it using right dependencies? Does it fit into broader design?
Which is expected for me and great help. I'm more happy as a human to spend less time checking if you're managing lifecycle of the pointer correctly and focus on ensuring that code is there to do what it needs to do.
The low quality of HN comments has been blowing my mind.
I have quite literally been doing what you describe every working day for the last 6+ months.
In our case, agentastic.dev, we just baked the code-review right into our IDE. It just packages the diff for the agent, with some prompt, and sends it out to different agent choice (whether claude, codex) in parallel. The reason our users like it so much is because they don't need to pay extra for code-review anymore. Hard to beat free add-on, and cherry on top is you don't need to read a freaking poems.
it's a valuable problem to solve, amplified by the fact that ai coding produces much more code.
that being said, i think it's damn hard to compete with openai or anthropic directly on a core product offering in the long run. they know that it's an important problem and will invest accordingly.
What do the vendors provide?
I looked at a couple which were pretty snazzy at first glance, but now that I know more about how copilot agents work and such, I'm pretty sure in a few hours, I could have the foundation for my team to build on that would take care of a lot of our PR review needs....
I get the idea. I'll still throw out that having a single X go through the full workflow could still be useful in that there's an audit log, undo features (reverting a PR), notifications what have you. It's not equivalent to "human writes ticket, code deployed live" for that reason
So, absolutely necessary and essential?
In order to get the machine out of trouble when the unavoidable strange situation happens that didn't appear during training, and requires some judgement based on ethics or logical reasoning. For that case, you need a human in charge.
- it will have higher chance at convincing the author that the issue was important by throwing more darts - something that a human wouldn't do because it takes real mental effort to go through an authentic review,
- it will sometimes find real big issue which reinforces the bias that it's useful
- there will always be tendency towards more feedback (not higher quality) because if it's too silent, is it even doing anything?
So I believe it will just add more round of back and forth of prompting between more people, but not sure if net positive
Plus PRs are a good reality check if your code makes sense, when another person reviews it. A final safeguard before maintainability miss, or a disaster waiting to be deployed.
still need HITL, but the human is shifted right and can do other things rather than grinding through fiddly details.
> Today's agents are better than the median human code reviewer
Which is it? You cannot have it both ways.
Can drop the extra words
> Based on our benchmarks, we are uniquely good at catching bugs. However, if all company blogs are to be trusted, this is something we have in common with every other AI code review product. One just has to try a few, and pick the one that feels the best.
Two that stood out to me are Sentry and Vercel. Both have released code review tools recently and both feel misplaced. I can definitely see why they thought they could expand with that type of product offering but I just don't see a benefit over their competition. We have GH copilot natively available on all our PRs, it does a great job, integrates very well with the PR comment system, and is cheap (free with our current usage patterns). GH and other source control services are well placed to have first-class code review functionality baked into their PR tooling.
It's not really clear to me what Sentry/Vercel are offering beyond what copilot does and in my brief testing of them didn't see noticeable difference in quality or DX. Feels like they're fighting an uphill battle from day one with the product choice and are ultimately limited on DX by how deeply GH and other source control service allow them to integrate.
What I would love to see from Vercel, which they feel very well placed to offer, is AI powered QA. They already control the preview environments being deployed to for each PR, they have a feedback system in place with their Vercel toolbar comments, so they "just" need to tie those together with an agentic QA system. A much loftier goal of course but a differentiator and something I'm sure a lot of teams would pay top dollar for if it works well.
Code review pressupose a different perspective, which no platform can offer at the moment because they are just as sophisticated as the model they wrap. Claude generated the code, and Claude was asked if the code was good enough, and now you want to be in the middle to ask Claude again but with more emphasis, I guess? If I want more emphasis I can ask Claude myself. Or Qwen. I can't even begin to understand this rationale.