I have experienced much of the opposite. With an established code base to copy patterns from, AI can generate code that needs a lot less iteration to clean up than on green fields projects.
That's a fair observation, there's probably a sweet spot. The difference I've found is that I can reliably keep the model on track with patterns through prompting and documentation if the code doesn't have existing examples, whereas I can't document every single nuance of a big codebase and why it matters.
I solve this problem by pointing Claude at existing code bases when I start a project, and tell it to use that approach.