How to review an AI-written pull request: a 10-point checklist
AI-written pull requests have a particular look. The code is tidy, the names are sensible, the description is confident, and the tests are green. That polish makes them easy to approve and harder to review well. The mistakes are still there. They just sit in different places than a rushed human change. Here's a checklist for the ten minutes you spend on an AI-written pull request, roughly in the…
Reviewing an AI-generated pull request requires a focused approach. First, read the task description to understand the original intent. Then, compare the diff against the task to ensure no extra changes were made. Pay attention to any deletions, as these can hide important issues. Examine the tests closely - they should validate the new functionality rather than just passing for the sake of it.
Check any new dependencies to ensure they are necessary and properly maintained. Verify the code handles errors and edge cases appropriately. Be wary of any unrecognised APIs or options, and confirm the solution doesn't introduce security vulnerabilities like hardcoded secrets. Finally, double-check that the commit you're approving is the one that will merge, and ensure all tests ran successfully on that specific commit.
By following this checklist, reviewers can ensure AI-generated code changes meet the same quality standards as those written by humans.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
