I think the temptation to use AI is so strong that it will be those who will keep learning who will be valuable in future. Maybe by asking AI to explain/teach instead of asking for solution direclty. Or not using AI at all.

On the other hand, if it's a one-off, you'll have forgotten what you learned by the time you'd need to use that skill again.

> I'm pretty sure AI is going to lead us to a deskilling crash.

That's my thought too. It's going to be a triple whammy

1. Most developers (Junior and Senior) will be drawn in by the temptation of "let the AI do the work", leading to less experience in the workforce in the long term.

2. Students will be tempted to use AI to do their homework, resulting in new grads who don't know anything. I have observed this happen first hand.

3. AI-generated (slop) code will start to pollute Github and other sources used for future LLM training, resulting in a quality collapse.

I'm hoping that we can avoid the collapse somehow, but I don't see a way to stop it.

I think seniors know enough to tell whether they need to learn or not. At least that's what I tell myself!

The thing with juniors is: those who are interested in how stuff works now have tools to help them learn in ways we never did.

And then it's the same as before: some hires will care and improve, others won't. I'm sure that many juniors will be happy to just churn out slop, but the stars will be motivated on their own to build deeper understanding.

On the contrary, being able to access (largely/verifiably) correct solutions to tangible & relevant problems is an extremely great way to learn by example.

It should probably be supplemented with some good old RTFM, but it does get us somewhat beyond the "blind leading the blind" StackOverflow paradigm of most software engineering.