I know for a fact I would not want to automate many of the predictable aspects of code reviews at any job I've ever had. This is because many of the predictable

I know for a fact I would not want to automate many of the predictable aspects of code reviews at any job I've ever had. This is because many of the predictable aspects of code review are due to poor review practices. Things like rubber-stamping review requests with a certain change size (e.g. lines of code, number of files), surface-level reviews (e.g. "yep this doesn't violate our style guidelines that the linter can't catch"), and similar items. A proper code review isn't simply catching API or style errors--it seeks to understand how the change affects the architecture and structure of the existing code. I'm sure AI can help with that, and for a broad class of changes it's likely somewhat to very predictable--but I'm skeptical that it is predictable for enough use cases to make it worth spending money on (for now), say. Put another way: "approves code reviews a human would have approved" isn't exactly the standard I'd want automated reviews to aspire to. Human approval, in my experience, is mostly not good quality reviews.