Notably, these walls are never where I expect them to be—despite my best efforts, I can't find any sort of pattern. LLMs can find really tricky bugs and get completely stuck on relatively simple ones.
Practically, though, how would someone become good at just the skills LLMs don't do well? Much of this discussion is about how that's difficult to predict, but even if you were a reliable judge of what sort of coding tasks LLMs would fail at, I'm not sure it's possible to only be good at that without being competent at it all.
This is, in fact, why we teach kids math that calculators could handle!
We don't teach kids how to use an abacus or a slide rule. But we teach positional representations and logarithms.
The goal is theoretical concepts so you can learn the required skills if necessary. The same will occur with code.
You don't need to memorize the syntax to write a for loop or for each loop, but you should understand when you might use either and be able to look up how to write one in a given language.
There are a growing set of problems which feel like using a calculator for basic math to me.
But also school is a whole other thing which I'm much more worried about with LLMs. Because there's no doubt in my mind I would have abused AI every chance I got if it were around when I was a kid, and I wouldn't have learned a damn thing.
And I hated mental math exercises as a kid.
That depends on if you ignore the future. You are never just solving the problem in front of you; you should always act in a way that propagates positivity forward in time.
Eventually, yes, I think we'll delegate to AI in more and more complete ways, but it's a process that takes some time.
Goes to the larger idea that strategic and logic is important for scalability and long term success. Not just execution. Something LLMs miss often (mostly because people fail to communicate it to them).
That being said, if you're writing in C, having a pretty good idea of how a cpu generally executes instructions is pretty key to success I'd say.
If you are a tiny startup, the marginal gains from these optimizations matter a lot less than if you are Netflix.
If at the first step I'm already dealing with a robot in the weeds, I will have to spend time getting it out of the weeds, all for uncertain results afterwards.
Now sometimes things are hard and tricky, and you might still save time... but just on an emotional level, it's unsatisfying