Apr 3, 2026
AI Code Review Workflow: Diff Viewer, Agent Handoffs, and Faster Merges
AI-generated changes are only as good as your review process. Build a repeatable AI code review workflow using structured diff inspection, reviewer agents, and traceable handoffs.
A strong AI code review workflow starts with one rule: always review diffs before trusting generated code. AI agents can move quickly, but speed without verification increases regression risk.
Review Loop Architecture
- Implementation agent proposes a change set.
- Reviewer agent checks logic, tests, and edge cases.
- Operator approves or requests revision.
Keep these lanes separate to avoid self-approval bias. Use one reviewer terminal that never edits files directly.
Tools That Improve Review Quality
- Diff Viewer for line-level validation.
- Git Visual Changes for branch-level awareness.
- Send File to Terminal for context-rich handoffs.
Review Checklist
- Does the diff satisfy the original acceptance criteria?
- Are tests updated or added where behavior changed?
- Did the change introduce hidden coupling or side effects?
- Can you roll back safely if production behavior regresses?
Visibility Matters
In multi-agent setups, quality drops when operators poll tabs manually. Use Activity Logs so review-ready events appear immediately.
Final Rule
Treat AI-generated code exactly like human-generated code: no merge without review. Structured diffs, reviewer lanes, and explicit handoffs are the fastest route to safe velocity.
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