This is my experience as well.

LLM currently produce pretty mediocre code. A lot of that is a "garbage in, garbage out" issue but it's just the current state of things.

If the alternative is noob code or just not doing a task at all, then mediocre is great.

But 90% of the time I'm working in a familiar language/domain so I can grind out better code relatively quickly and do so in a way that's cohesive with nearby code in the codebase. The main use-case I have for AI in that case is writing the trivial unit tests for me.

So it's another "No Silver Bullet" technology where the problem it's fixing isn't the essential problem software engineers are facing.