By that logic, if modern LLMs existed in the 80s, you’d have never learned Haskell, Ocaml, Rust, Go, Erlang, … and all the cool concepts and ideas that came with them. You’d still be programming Basic and Fortran, simply because that’s all the models knew.
AI may be helpful at times, but to limit one’s self to only the knowledge and experience they have is… short sighted at best.
You got a point here however I would just flip his argument. It is best to rely on LLMs that have a lot of training data exposure, and here is Python etc. dominating over Delphi.
I for example find LLMs not useful in regards to coding on 6510 or 68000 especially in assembler when developing code for a product of the demo scene.
x86 became pretty useful lately, but still, on certain machines with bit manipulation, you would better take your time to triple check your code and don't rely on LLM.
Unfortunately this is what AI is leading to. People will stop learning new languages and companies will stop developing new ones because AI is now supposed to write code.
I tried to make some LLMs write (GW-)BASIC and they failed miserably. Maybe they were only trained on some modern BASIC that doesn't look like BASIC at all? Could not convince them to use line numbers at all. Maybe with a lot of context they could do it, but my prompts did not work, even making I clear I wanted line numbers.
(Free)Pascal seems to work great though. I think enough of that is in training data that it can be used as well as any language. There isn't much special to consider to get it right. It is not like figuring out how to do Rust or C++.
You might be right. Have you seriously considered that you're wrong though? What if you're investing a dead craft and it never pays off? have you engaged with that idea and rejected it?
Regarding the former, I’m nearing retirement age, so personally I don’t care as much; I’m no longer “investing [in] a dead craft”. Assuming it is dead (I don’t think it is).
Re the latter, I have rejected it. I love problem solving. And I consider programming a tool I use to solve problems. Regardless of whether it’s an LLM or my old C text book, if I limited myself to only what came before me, then I can’t possibly improve on the current situation. My solutions would be in a perpetual state of stagnation. I can’t speak for others, but that sounds boring AF to me.
So then it's a life stage thing. You're already well established in your career, and you'd rather some intellectual engagement. There's nothing wrong with that.
A 22 year old fresh out of undergrad almost certainly wants actual money far more than they want intellectual engagement. Most of them are better served by picking up a boring workhorse language that they can reliably get paid to write. Inevitably some will speciate into more esoteric fields, but that's the exception, not the rule.
AI may be helpful at times, but to limit one’s self to only the knowledge and experience they have is… short sighted at best.