High-Signal AI PR Review Checklist (Without Slowing Engineers)
A review checklist that catches real risk in AI-assisted pull requests while keeping throughput high.
February 12, 2026 · 7 min read
Review for risk, not prose
AI can generate polished code that still violates invariants. Review should target failure modes:
- data integrity
- auth boundaries
- error handling and retries
- side effects and idempotency
5-point checklist
1) Contract safety
Are external and internal contracts unchanged or explicitly versioned?
2) Failure behavior
Do failures degrade safely? Look for swallowed exceptions and silent retries.
3) Test intent
Do tests prove behavior or just execute lines? Ask for at least one failure-path test.
4) Security defaults
Input validation, secrets handling, and access checks should be explicit.
5) Operational clarity
Can on-call understand this change from logs/metrics alone?
Team pattern that works
Use “AI-generated diff note” in PR template:
- what assistant generated
- what human verified
- known limitations
This raises accountability without banning AI-generated code.