New blog post: ai-based code review#1107
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posts/code-review/index.md
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| ## [Gemini-code-assist](https://github.com/marketplace/gemini-code-assist) | ||
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| Our AI tool of choice for our upstream reviews is Gemini-code-assist. It's free, easy to set up, and you get to see the comments inside the GitHub interface. Since it's powered by the Gemini models, it can provide solid feedback. If your PR contains clear mistakes, this tool can easily find them. |
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If your PR contains clear mistakes, this tool can easily find them.
My feeling is that we revealed with it not only clear mistakes, but also more subtle ones, and it definitely prevented lot of bugs from getting into production. But curious what do others think.
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Agreed, sometimes it can find very non-obvious issues.
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amazing feedback, I'll incorporate it
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| I'd say the biggest downside of this tool is that you need to open a PR to see the feedback, you cannot run it locally. |
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I would maybe also mention the related advantage, that it can encourage the team to align on technical debt or complex logic that the tool brings up as a review comment.
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| This tool can be infinitely helpful, especially if your codebase is easy to navigate, is not colossal, and has solid documentation which Claude can follow. | ||
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| Several people on the team use Claude Code daily and it is part of our daily job. We've gotten used to it so much that we couldn't live without it, honestly. It's so convenient and helpful. |
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oh true, let me add that info there
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For sake of running script `files/generate_usage.py` Signed-off-by: Tomas Tomecek <ttomecek@redhat.com>
Signed-off-by: Tomas Tomecek <ttomecek@redhat.com> Assisted-by: Claude
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| # Our experience with AI-based code review | ||
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| One amazing benefit that modern LLMs come with is using them as a linter, or a pair programmer. You can easily get feedback on your code with such an approach. If the feedback is solid, your code is improved. If the review is poor, you can just disregard it. But overall with very little effort you can gain a lot. |
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You can easily get feedback on your code with such an approach.
Is this supposed to be interpreted as using the LLM?
you can just disregard it
or prompt again…
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improved the first paragraph to address the first comment, but second is silently implied, we don't need to be pixel-perfect here :)
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Co-authored-by: Laura Barcziová <49026743+lbarcziova@users.noreply.github.com> Co-authored-by: Nikola Forró <nforro@redhat.com> Co-authored-by: Maja Massarini <mmassari@redhat.com> Co-authored-by: Matej Focko <mfocko@users.noreply.github.com> Signed-off-by: Tomas Tomecek <ttomecek@redhat.com> Assisted-by: Claude
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You are very welcome to share your perspective with AI-powered code review because I tried to write it as it's a team effort.