# AI code review

**Source:** https://promtable.com/glossary/ai-code-review

> AI code review is the automated PR-review workflow where an LLM agent reads a diff, identifies bugs / regressions / style issues, and posts inline comments — CodeRabbit, GitHub Copilot Review, Greptile, Coderabbit, Trag are 2026 leaders.

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AI code review is the automated PR-review workflow where an LLM agent reads a diff, identifies bugs / regressions / style issues, and posts inline comments — CodeRabbit, GitHub Copilot Review, Greptile, Coderabbit, Trag are 2026 leaders.

Traditional CI catches syntax + types + tests; AI code review fills the gap between 'compiles' and 'human reviewer would catch this'. Workflows: PR opened → webhook fires → agent fetches diff + relevant codebase context (often via [[graph-rag]] or repo embeddings) → LLM identifies issues → comments posted inline. Production tools in 2026: CodeRabbit (most mature), GitHub Copilot Review (native), Greptile (deep context), Trag (custom rules), Korbit. Quality: catches obvious bugs (null derefs, off-by-one, missing await), misses subtle architecture issues. Best used as a first-pass filter freeing human reviewers for design + intent. Worst when noisy — every PR with 30 low-signal comments trains the team to ignore reviews.

## When to use

- First-pass review on PRs.
- OSS projects without maintainer bandwidth.

## Common mistakes

- Treating AI review as final review — humans still catch design issues AI misses.
- No noise calibration — review fatigue is real.

## Related terms

- [pull-request-bot](https://promtable.com/glossary/pull-request-bot)
- [background-agent](https://promtable.com/glossary/background-agent)
- [evals](https://promtable.com/glossary/evals)

*Last updated: 2026-06-01*
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Original page: https://promtable.com/glossary/ai-code-review
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