Comment by Wowfunhappy 2 days ago
Sometimes you hit a wall where something is simply outside of the LLM's ability to handle, and it's best to give up and do it yourself. Knowing when to give up may be the hardest part of coding with LLMs.
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.
I agree, and I can actively feel myself slipping (and perhaps more critically, not learning new skills I would otherwise have been forced to learn). It's a big problem, but somewhat orthogonal to "what is the quickest way to solve the task currently in front of me."
> but somewhat orthogonal to "what is the quickest way to solve the task currently in front of me."
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.
The thing i struggle with is I feel like it’s hard to lock into which skill to learn properly. Which so much changing so quickly and it becoming easy to learn things superficially.
Moving up abstraction layers really only succeeds with a solid working knowledge of the lower layers. Otherwise, you're just flying blind, operating on faith. A common source of bugs is precisely a result of developers failing to understand the limits of the abstractions they are using.
So we can all only succeed if we know how CPUs handle individual instructions?
Should we not teach kids math because calculators can handle it?
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.
> Should we not teach kids math because calculators can handle it?
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.
Should you never use a calculator because you want to keep your math skills high?
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.
> 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!
Sure, I agree with the "levels of automation" thought process. But I'm basically experiencing this from the start.
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
Doing it yourself is how you build and maintain the muscles to do it yourself. If you only do it yourself when the LLM fails, how will you maintain those muscles?