dakshgupta

Joined 4 years ago

Karma
1,123
Submissions
201
Member since
May 18
Co-founder at Greptile.com.
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Recent submissions

Comment · 4 months ago
Apart from the job-related stuff others have already said, there is a bit of novelty/bragging rights in landing a PR into a major open source project.
Comment · 4 months ago
Not yet - but we want to do this. Similarly true for the ephemeral unit tests that greptile writes.
Comment · 9 months ago
The signal-to-noise ratio problem is unexpectedly difficult.

We wrote about our approach to it some time ago here - https://www.greptile.com/blog/make-llms-shut-up

Much has changed on our approach since then, so we'll probably write a a new blog post.

The tl;dr of what makes it hard is - different people have different ideas of what a nitpick is - it's not a spectrum, the differences are qualitative - LLMs are reluctant to risk downplaying the severity of an issue and therefore are unable to usefully filter out nits. - theory: they are paid by the token and so they say more stuff

Comment · 9 months ago
Comment · 9 months ago
I agree that none perform _super_ well.

I would argue they go far beyond linters now, which was perhaps not true even nine months ago.

To the degree you consider this to be evidence, in the last 7 days, the authors of a PR has replied to a Greptile comment with "great catch", "good catch", etc. 9,078 times.

Comment · 9 months ago
2. There is plenty of evidence for this elsewhere on the site, and we do encourage people to try it because like with a lot of AI tools, YMMV.

You're totally right that PR reviews go a lot farther than catching issues and enforcing standard. Knowledge sharing is a very important part of it. However, there are processes you can create to enable better knowledge sharing and let AI handle the issue-catching (maybe not fully yet, but in time). Blocking code from merging because knowledge isn't shared yet seems unnecessary.

Comment · 9 months ago
> Independence

It is, but when a model/harness/tools/system prompts are the same/similar in the generator and reviewer fail in similar ways. Question: Would you trust a Cursor review of Claude-written code more, less, or the same as a Cursor review of Cursor-written code?

> Autonomy

Plenty of tools have invested heavily in AI-assisted review - creating great UIs to help human reviewers understand and check diffs. Our view is that code validation will be completely autonomous in the medium term, and so our system is designed to make all human intervention optional. This is possibly a unpopular opinion, and we respect the camp that might say people will always review AI-generated code. It's just not the future we want for this profession, nor the one we predict.

> Loops

You can invest in UX and tooling that makes this easier or harder. Our first step towards making this easier is a native Claude Code plugin in the `/plugins` command that let's Claude code do a plan, write, commit, get review comments, plan, write loop.

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