We noticed this and spent a week or two going through and cleaning up tests, UI components, comments, and file layout to be a lot more consistent throughout the codebase. Codebase was not all AI written code - just many humans being messy and inconsistent over time as they onboard/offboard from the project.

Much like giving a codebase to a newbie developer, whatever patterns exist will proliferate and the lack of good patterns means that patterns will just be made up in an ad-hoc and messy way.

This is it right here. Claude loves to follow existing patterns, good or bad. Once you have a solid foundation, it really starts to shine.

I think you're likely in the silent majority. LLMs do some stupid things, but when they work it's amazing and it far outweighs the negatives IMHO, and they're getting better by leaps and bounds.

I respect some of the complaints against them (plagiarism, censorship, gatekeeping, truth/bias, data center arms race, crawler behavior, etc.), but I think LLMs are a leap forward for mankind (hopefully). A Young Lady's Illustrated Primer for everyone. An entirely new computing interface.

I legit think this is the biggest danger with velocity-focused usage of these tools. Good patterns are easy to use and (importantly!) work! So the 32nd usage of a good pattern will likely be smooth.

The first (and maybe even second) usage of a gnarly, badly thought out pattern might work fine. But you're only a couple steps away from if statement soup. And in the world where your agent's life is built around "getting the tests to pass", you can quickly find it doing _very_ gnarly things to "fix" issues.

You haven't answered the question though. Are your code peer reviewed? Are they part of client-facing product? No offense, I like what you are doing, but I wouldn't risk delegation this much workload in my day job, even though there is a big push towards AI.