Saw a recent talk where someone described AI as making errors, but not errors that a human would naturally make and are usually "plausible but wrong" answers. i.e. the errors that these AI's make are of a different nature than what a human would do. This is the danger - that reviews now are harder; I can't trust it as much as a person coding at present. The agent tools are a little better (Claude Code, Aider, etc) in that they can at least take build and test output but even then I've noticed it does things that are wrong but are "plausible and build fine".
I've noticed it in my day-to-day: an AI PR review is different than if I get the PR from a co-worker with different kinds of problems. Unfortunately the AI issues seem to be more of the subtle kind - the things if I'm not diligent could sneak into production code. It means reviews are more important, and I can't rely on previous experience of a co-worker and the typical quality of their PR's - every new PR is a different worker effectively.
I've noticed it in my day-to-day: an AI PR review is different than if I get the PR from a co-worker with different kinds of problems. Unfortunately the AI issues seem to be more of the subtle kind - the things if I'm not diligent could sneak into production code. It means reviews are more important, and I can't rely on previous experience of a co-worker and the typical quality of their PR's - every new PR is a different worker effectively.