Cubic: Enhanced Code Review Cursor

Paul, cofounder of cubic—an “AI-native GitHub”—describes the evolution of their AI code review agent, which was initially criticized for excessive noise and irrelevant comments in pull requests. Following substantial user feedback, the team undertook three major architecture revisions to reduce false positives by 51% without compromising the system’s recall. Key improvements included implementing explicit reasoning logs, which clarified the AI’s decision-making process, and streamlining the toolkit to focus on essential tools only. They also transitioned from a generalized agent to specialized micro-agents, each addressing specific issues like security and code duplication. These changes led to a reduction in median comments per PR by half, enhancing overall review efficiency. Ultimately, the adjustments improved developer trust, engagement, and streamlined review processes, demonstrating broader lessons for AI design: the value of clarity in reasoning, simplicity in toolsets, and specialization in functionality.

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