Until you physically see it running learning is slow.

I learned k8s through many months of study and pain pre AI. Once I actually got it up learning was FAR easier.

This is like using a jupyter notebook to learn python and is always the first thing I point to for someone just starting to learn. Only after should you learn venv, pip install, classes ect.

100% use AI to get started on something you don't understand. I will literally never start to learn about a technical system again without first doing a hello world with AI.

I mostly agree it's an area that's risky to wander into mindlessly but it is much more easier to validate knowledge than to practice it.

E.g. I can't write Chinese but can validate if piece of Chinese is a valid one (by feeding to N translators, other LLMs or asking a friend who knows Chinese).

Under assumption of "LLM output is false until proven otherwise" it's not a bad approach and worked for me in various scenarios. (E.g. I asked for implementation of algorithm in Rust and then validated it against base definition).

We all have different learning styles. I learn through play when it comes to LLMs.