For me personally, there is only two applications of LLMs in programming:

• doing tasks I kinda know how to do, but don't want to properly learn (recent example: generate pgf plots from csv data in matplotlib. 90% boilerplate, I last had to do it 3 years ago and vaguely remember some pitfalls so can steer the LLM in that direction. Will probably never again have to do this, so not worth the extra couple hours to properly learn
• things I would ordinarily write a script for, but aren't worth automating because they won't come up in the future again (example: convert this Lua table to a Nix set)

Essentially, one-off things that you know how to check for correctness.

Same here (15 years). I work in all sorts of frameworks and languages. I normally would have just googled a given question to see the code i need, paste it in with everything that's wrong, and fix it to my liking. I know what I'm doing I was just missing the specific words i havent used in a couple years, i still understand them. Copilot just avoid me opening google, clicking through some bad SEO, passing the bad answers, and doing that a couple more times to bring in everything I need. It's a google formatter.

It's also exactly like searching google. If you ask "is this cancer" you'll find cases where it's cancer, if you ask "is this not cancer" youll find cases where it's cancer. You can't trust it in that way, but you can still quickly parse the internet. I make juniors explain their code so even if they paste it in, they're kind force to research it more to make sure they get it; it's on the reviewers now to train llm kiddos.