Ironically, AI mitigates bad developers quite a bit. The architecture/design is coming from above bad devs (in a functional org), and AI tends to write less sloppy code than bad devs, and test/validate it more rigorously.
If you're a good dev, you can totally prompt Claude to not do this and correct itself, that's not an issue. The issue is that bad devs won't even notice this is happening in the first place.
At my org we use Github Copilot as our AI tool for devs, both internally and for vendors (Including a WITCH =/).
Where it gets ugly, is that we have a -lot- of WITCH provided code already in our systems, and as a result GHCP winds up often preferring the existing (terrible) patterns.
I've done some things to help mitigate at least; Adding instruction/skill/agent files, tossing in some LLM-built .NET analyzers to catch the worst anti-patterns to warn on build and error on CI, and making sure to call out when the vendor people are obviously not even reviewing what the LLM generated for them [0]
[0] - Simplest case being, EF Core mappings where the datatypes do not even exist in the target DB...
I've often had it test and benchmark against the wrong things = no test.
It also writes over-engineered code. So yes sort, maybe.