A team at Aviator discovered that traditional code review processes don't scale effectively when AI generates a significant portion of the code. They shifted away from line-by-line diff reviews, instead focusing on verifying intent, acceptance criteria, invariants, decisions, and evidence. This approach allowed them to merge pull requests four times faster, reduce review times, and decrease reverts, highlighting the importance of knowledge sharing and decision-making in the review process. Teams should consider how to structure AI-assisted code review to prioritize higher-level context and reasoning.
Read the full article at The New Stack
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