AI coding tools make it much cheaper to produce a first draft.
But they do not remove the need for review discipline.
A simple rule I like:
If AI materially helped write a pull request, run a structured AI review before asking a human reviewer.
Ask the assistant to check:
- goal fit
- unnecessary scope expansion
- logic errors
- edge cases
- API/contract changes
- security and privacy risks
- data integrity risks
- performance concerns
- weak or missing tests
- maintainability
- rollback risk
The key is not:
review this code
The better instruction is:
Review this PR like a strict senior engineer. Return the top risks, specific review comments, missing tests, and missing context before this should be merged.
AI review is not approval.
It is a cleanup pass before human review.
Full checklist and copy-paste prompt:
https://dev.to/suifeng023/the-ai-code-review-checklist-a-copy-paste-prompt-for-safer-pull-requests-5n
If you want a larger developer prompt library for code review, PRs, debugging, architecture, and AI coding workflows, I also sell the Developer's Prompt Engineering Bible here:
Top comments (0)