It's for new things: new languages, frameworks, libraries. When you're not fluent, it can be a helpful hand for a beginner, or someone who has to do a lot things that they are not expert in, like a one man band in a sole enterprise or corner of a startup.

It can increase efficiency for generalists. For deep work, it's less useful.

I agree. That so far the super specialist can do better. But they will also find useful when they need to cross the domain that are good at with something that they are yet a beginner. Also, for mechanical things, it is amazing. Like, for helping solving a conflict of a patch with a context, or editing lots of parts in a code with something that it would require multiple regexps.

I agree with your experience, and am curious as to what the difference between the two scenarios is.

I always wanted to do this very specific in Django. I don't work with Python,so even though I knew what I want to do,but my skills weren't there to create working code. So I thought I'll throw the problem at chatGPT. The generated code had a couple of flaws, but I managed to fix them in 15 min or so and got a working result. The code also gave me some interesting perspective on how some things could be implemented.

That’s interesting since I threw some questions at it about Django and I didn’t think it gave very idiomatic patterns for it.

What it generated in Django was very simple and likely far from the quality an experienced engineer would come up with, but at my knowledge level that was enough.

If you iterate and ask it to provide more idiomatic patterns, it will!