Common Code Review Mistakes and Best Practices for Engineers
By
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Summary
The article discusses common mistakes engineers make in code reviews, particularly in the era of AI-generated code. The author argues that focusing solely on code diffs is a major error, and emphasizes the importance of understanding the broader context, business requirements, and overall system architecture during code reviews. The piece provides practical advice for improving code review practices, highlighting how the rise of LLMs has changed the review process while the fundamental challenges remain.
Key quotes
· 4 pulledIn the last two years, code review has gotten much more important. Code is now easy to generate using LLMs, but it's still just as hard to review.
Many software engineers now spend as much (or more) time reviewing the output of their own AI tools than their colleagues' code.
The biggest mistake I see is doing a review that focuses solely on the diff.
I think a lot of engineers don't do code review correctly. Of course, there are lots of different ways to do code review, so this is largely a statement of my engineering taste.
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