With human co-workers, you can generally assume things you can't with AI.

My human co-workers generally have good faith. Even the developer who was clearly on the verge of getting a role elsewhere without his heart in it-- he tried to solve the problems assigned to him, not some random delusion that the words happened to echo. I don't have that level of trust with AI.

If there's a misunderstanding the problem or the context, it's probably still the product of a recognizable logic flow that you can use to discuss what went wrong. I can ask Claude "Why are you converting this amount from Serbian Dinars to Poppyseed Bagels in line 476?" but will its answer be meaningful?

Human code review often involves a bit of a shared background. We've been working with the same codebases for several years, so we're going to use existing conventions. In this situation, the "AI knows all and sees all" becomes an anti-feature-- it may optimize for "this is how most people solve this task from a blank slate" rather than "it's less of a cognitive burden for the overall process if your single change is consistent with 500 other similar structures which have been in place since the Clinton administration."

There may be ways to try to force-feed AI this behaviour, but the more effort you devote to priming and pre-configuring the machine, the less you're actually saving over doing the actual work in the first place.