Are you actually learning the concepts though? I'm not trying to be inflammatory but a lot of people I see using LLM use them as a replacement for StackOverFlow. They aren't learning anything they just need it to spit out code that works.
I am constantly using AI to learn more every day -- and learning at a faster rate than I was just pouring through the internet for those same answers.
I'm not just using it to generate code, but asking specific questions. Even really basic stuff like, write me a Fibonacci number generator in X language. Helps me understand the syntax immediately. I can start from a place of familiarity. A lot of times when picking up a new language, the hello world stuff is kind of drawn out. Give me a program in Rust that generates 50 random numbers and sort it from smallest to biggest. Give me the basic framework for a Flask app, etc etc.
Or, I have an app that scrapes a website. What is the best architecture to put this into a database to reduce scraping the same thing multiple times?
I use it like a project manager/software architect/tutor in that order I think.
It massively reduces the friction to just getting things going.
As for AI specifically, robust testing is already difficult with human-curated logic. It's potentially more likely to miss failing cases, or non-binaries (e.g. performance, security), when testing genAI. More subjectively, your conjecture represents a mindset that is demotivating to people with certain flavors of creativity/passion. Also, overreliance on AI may blunt skills that may remain useful, and even important - i.e. it may exacerbate an expertise scarcity.
(this may make me sound more negative on AI that I am - remember that I'm commenting in the context of the post you're replying to)