> and you'll never be able to escape it.

Slow down, cowboy. Getting a LLM to generate code for you that is immediately useful and doesn't require you to think too hard about it can stunt learning, sure, but even just reading it and slowly getting familiar with how the code works and how it relates to your original task is helpful.

I learned programming by looking at examples of code that did similar things to what I wanted, re-typing it, and modifying it a bit to suit my needs. From that point of view it's not that different.

I've seen a couple of cases first hand of people with no prior experience with programming learn a bit by asking ChatGPT to automate some web scraping tasks or spreadsheet manipulation.

> You + limited knowledge of Python + ChatGPT << someone + good knowledge of Python + ChatGPT.

Substract ChatGPT from both sides and you have a rather obvious statement.

> Respectfully but that's a bit like saying you don't need to learn how to ride a bicycle because you can use a pair of safety wheels.

How did you learn to ride a bicycle?

I actually disagree with this. One of my few really helpful LLM experiences is working with technologies that I rarely touch. nginx configs are probably a good example, or a library I haven't touched in 5 years.

The AI is pretty good at answering "I know this is possible, remind me what it's called or what the syntax is."

For a lot of these the reason I want to look it up is I don't use it enough to build muscle memory. If I did, I'd already have the muscle memory. And in practice, it's just a faster version of looking for examples on stackoverflow.

> Respectfully but that's a bit like saying you don't need to learn how to ride a bicycle because you can use a pair of safety wheels.

Do you care how a car engine works to drive a car?

Respectfully, this is an incredibly weak take.

You are making a lot of assumptions about someone's ability to learn with AND without assistance, while also making rather sci-fi leaps about our brain somehow being able to differentiate between learning that has somehow been tainted by the tendrils of ML overlords.

The models and the user interface around them absolutely will continue to improve far faster than any one person's ability to obtain subject mastery in a field.

I'm long time programmer and I learned quite a lot of languages along the way. 20 years ago I programmed Perl and I spent some time learning its quirks. While some of that knowledge definitely helped me all these years, especially regular expressions, I wouldn't write a single Perl line without Googling today.

So learning syntax nuances of yet another programming language which I'll forget soon is wasted time. There's some "fundamental" knowledge, like understanding what functional value is, but the specific syntax that Python invented for lambda - that's not something valuable when I use Python few times a year.