This is about how I use it. I initially use it to carve out an architecture and iterate through various options. That saves a lot of time for me having to iterate through different language features and approaches. Once I get that, I have it scaffold out, and I go in and tidy things up to my personal liking and standards. From there, I start iterating through implementations. I generally have been implementing stuff myself, but I've gotten better at scaffolding out functions/methods through code instead of text. Then I ask it to finish things off. That falls into your first category of letting it implement stuff that I already know I could do. Not sure if it's faster. But it's lower cognitive load for me, since I can start thinking about the next steps without being concerned about straightforward code.

This all works pretty great. Where it starts going off the rails is if I let it use a library I'm not >=90% comfortable with. That's a good use of these tools, but if I let it plow through feature requests, I end up accumulating debt, as you pointed out.

For my uses, I'm still finding the right balance. I'm not terribly sure it makes me faster. What I do think it helps with is longer focused sections because my cognitive load is being reduced. So I can get more done but not necessarily faster in the traditional sense. It's more that I can keep up momentum easier, which does deliver more over time.

I'm interested in multi agent systems, but I'm still not sure of the right orchestration pattern. These AI tools still can go off the rails real quick.