AI Code Review Tools Compared
We tested five AI code review tools on the same set of pull requests. The results were more nuanced than the marketing pages suggest.
AI-powered code review is one of the most promising applications of LLMs in development workflows. We tested five tools across 40 real pull requests from three active projects.
The contenders
We evaluated CodeRabbit, Sourcery, Codium, GitHub Copilot code review, and Cursor's review mode. Each was run against the same PRs with default settings.
What we measured
We tracked three things: true positive rate (real issues caught), false positive rate (noise), and actionability (could a developer act on the feedback without additional context).
Key findings
No tool caught more than 60% of the issues a senior developer flagged. But every tool caught at least one issue the human reviewer missed. The tools complement human review — they don't replace it.
CodeRabbit had the best signal-to-noise ratio. Copilot generated the most comments but also the most false positives.
Our recommendation
Use AI code review as a first pass, not a final gate. Configure it to focus on your most common bug categories and suppress the rest.