Yes. AI-generated code should be reviewed before merging, just like human-authored code, and often with extra attention to hidden assumptions, broad changes, and weak tests. Generation speed does not reduce the impact of a defect after release.
Review the diff against the requirement first. Confirm that it stays in scope, follows project conventions, handles errors, and does not expose secrets or weaken authorization. Inspect new dependencies, migrations, configuration, and generated tests. Run the focused tests, then the full required checks. For high-risk changes, use a second reviewer or security specialist.
AI review can help identify issues, but it should not be the only approval. A model may share the author's blind spots or accept plausible but incorrect behavior. Separate implementation and review contexts where possible, and require concrete evidence for important findings.
Verdent's Reviewer and worktree-based isolation can support a controlled handoff from agent output to approval. Teams can encode standards in project or review rules. The person merging the code remains accountable for the result. If the reviewer cannot explain what changed and why the checks are sufficient, the code is not ready to merge.
