A coding agent can open a pull request in minutes. The reviewer still has to decide whether the change solves the right problem, whether it is safe to operate and who will maintain it. A clean diff and a green test run help, but neither answers all three questions. Consider a request to add a retry to a payment client. The agent may produce tidy code, add a unit test and describe the change accurately.

The promise was efficiency. Feed the prompt, review the output, merge the diff. What teams discovered instead is that AI-assisted code review is more cognitively demanding than reviewing code written by a colleague — not less — because the nature of the errors has changed. When a human writes a bug, there is usually a traceable cause: a misunderstood requirement, a missed edge case, a copy-paste error. The bug has an author with intent.