Claude's code review skill, in particular, can find some good stuff. But it has some big blind spots around certain types of code. And it likes to come up with a lot of nits too—I think it's really really trained to try to always find between 2 and 8 things or somesuch. Good news is that it is very receptive to "nah" on the bikeshed ones and doesn't stick with them, but will stick with big issues. It'll probably bring up a few more nits though that it didn't bring up the first time!

But I can completely believe that someone who knows the code by heart would have a better signal to noise ratio on their reviews.

I'm trying to find the sweet spot because I've found some NASTY bugs Claude missed, and also had Claude find some nasty ones for me. And this is in codebases with tens-of-thousands of AI-generated lines of code + AI-driven reviews. So I want to bring both to the table.

The existence of some of these major "oh man that changes a lot of our assumptions" bugs that were only found because someone poked on the agent and said "I don't think you're paying enough attention to this" justifies that, IME.

And the better you are at pointing the agent at the truly-important parts, the better the agent's gonna be at finding shit you missed.

Claude's code review is a lot less interesting then getting Claude to reproduce the bugs it claims to find in code review, which has had an absurdly high hit rate for me.

The biggest problem I see with how a bunch of people use these tools is they go to them as an oracle, rather then letting them be plugged into and interactive with problem.

And it's in that later context that Claude is amazing: it can run tests and setup scenarios which would take days or get stuck in some weird problem loop. And then you can just say "okay, walk me through this problem" and see it yourself right there.