Yeah, I think about this a lot.

Those days of grinding on some grad school maths homework until insight.

Figuring out how to configure and recompile the Linux kernel to get a sound card driver working, hitting roadblocks, eventually succeeding.

Without AI on a gnarly problem: grind grind grind, try different thing, some things work, some things don't, step back, try another approach, hit a wall, try again.

This effort is a feature, not a bug, it's how you experientially acquire skills and understanding. e.g. Linux kernel: learnt about Makefiles, learnt about GCC flags, improved shell skills, etc.

With AI on a gnarly problem: It does this all for you! So no experiential learning.

I would NOT have had the mental strength in college / grad school to resist. Which would have robbed me of all the skill acquisition that now lets me use AI more effectively. The scaffolding of hard skill acquisition means you have more context to be able to ask AI the right questions, and what you learn from the AI can be bound more easily to your existing knowledge.