Ask HN: How is your org managing PR review load as AI multiplies code output?
The article discusses strategies for managing pull request (PR) reviews in the context of increased code output due to AI. It emphasizes the importance of reciprocation and effective communication during the review process. The author shares their approach to reviewing code based on its quality and the responsiveness of the developer.
- ▪The author reviews code diligently if it is reasonable and well-created.
- ▪For unreadable code, the author uses AI to review and shares the output without personal review.
- ▪The author engages in constructive feedback for middling quality code and seeks collaboration.
Opening excerpt (first ~120 words) tap to expand
I have a few strategies - which are all based on reciprocation.If the code is reasonable and diligently created, be it with AI or not, I will provide a diligent and timely review.If the code is totally unreadable AI slop that does not appear to have been read by the person who created the PR, I will use AI to review the code and share the output, without reading it.If the code is of middling quality, I will find one or two token areas that could use improvement, and suggest a better alternative like "How about doing this with 2 syscalls instead of 4?" or "How about refactoring this duplicated code into a method, and calling the method?", or whatever. If the person responds intelligently, I will proceed to review the rest of the code and work together.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Ycombinator.