How do you manage quality when AI agents write code faster than humans can review it?
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A developer community discusses the challenge of maintaining code quality when AI agents generate code faster than humans can review it. One perspective suggests shipping code at the agents' production speed, as that is their primary purpose. A current approach involves using tools like bugbot and coderabbit to gate every pull request for an initial review, with humans focusing on escalated issues and critical areas like financial or authentication code. This method helps manage the volume, but its effectiveness in maintaining overall quality is still being evaluated.
We moved to an agentic workflow this quarter. My position is that we should ship at whatever speed the agents can produce, since that is the entire point of paying for them.
Our CTO's counter is that a team can only safely absorb code as fast as it can read it. If agents 10x the volume, review becomes the bottleneck that decides everything, and he thinks the tech debt won't show up as bad code, it will show up as code nobody on the team can explain.
The middle ground we're testing right now: bugbot / coderabbit gates every PR for a first pass, and humans only deep-read what it escalates plus anything touching money or auth. It definitely helps with the volume. What I can't tell yet is whether we're managing quality or just measuring less of it