In my opinion, the most useful way to use LLMs for learning (anything, but including programming) is to have it explain things in terms of what you are familiar

In my opinion, the most useful way to use LLMs for learning (anything, but including programming) is to have it explain things in terms of what you are familiar with. You can give the model context of things you know are relevant that you do understand (or at least have a functional understanding of), and ask it to explain things that you don't yet understand, building on what you know. For example, asking things like "I am familiar with object encapsulation and mutating state over time in object oriented programming. If pure functional programming does not allow for mutation, how to you manage the state of objects over time?" or "Help me learn about Kubernetes. I am familiar with using docker, docker compose, and virtual machines for deploying my applications." The problem is when you're learning something completely foreign like learning to program in your first language, you don't really have enough context to ask meaningful questions. In that case, it is simply better to do things like read manuals and bang your head against the problem.