AI in code review: benefits, limits and responsibility
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AI works well as a code review assistant when it helps raise questions. It should not be the final authority on whether a change is safe and business-correct.
What AI notices well
AI tools such as OpenAI (opens in a new tab) and Anthropic (opens in a new tab) can quickly find repetition, inconsistent patterns and places where reviewers should ask more questions.
In code review, AI helps:
- summarise a large diff;
- find missing error handling;
- compare a change with existing patterns;
- suggest test cases;
- notice missing documentation.
Where responsibility stays human
AI does not always know the project history, client workflow or server constraints. It can suggest a solution that is theoretically correct but wrong in this project.
WebPro uses AI as an assistant in Drupal work, combined with tests and developer review. If a change affects a business-critical feature, it should have automated testing or at least a clear manual test plan.
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