Comment by alecco
3 days ago
Speak for yourself. I now dare to code much harder problems and learning is bliss. No more having to sit down to dig needle-in-haystack through horrible documentation or random Stack Overflow posts.
LLMs are a magnificent tool if you use them correctly. They enable deep work like nothing before.
The problem is the education system focused on passivity (obeyance), memorization, and standardized testing. And worst of all, aiming for the lowest common denominator. So most people are mentally lazy and go for the easy win, almost cheating. You get school and interview cheating and vivecoders.
But it's not the only way to use LLMs.
Similarly, in Wikipedia you can spend hours reading banal pop-slop content or instead spend that time reading amazing articles about history, literature, arts, and science.
Perhaps the approach to, and leverage from, using AI is different for someone who's been active on HN for two decades, and junior devs who've been brought up on iPhones in the flawed school system you're describing?
As TFA says, the problem is that accumulating knowledge takes time and effort, and the AI hype and expectations on LLM-assisted coding helps with rationalizing ever more short-sighted decisions that squander or hinder that process.
> Speak for yourself.
Even if you are the absolute unicorn who gets paid to "code much harder problems" and "learning", the rest of the industry exists to deliver actual products and services.
So unless you nurture some type of https://xkcd.com/208/ fantasy, this is not just about you. The industry as a whole needs to find a way to work with LLMs without automating programming away entirely, and the industry as a whole needs to find a way to ensure that newcomers are able to be productive even if code-generation tools are taken away from them.
> in Wikipedia you can spend hours reading banal pop-slop content or instead spend that time reading amazing articles about history, literature, arts, and science.
I'm not saying you're personally doing anything wrong, but there's a parallel here, when smart and curious people read articles about history and literature and art and science, rather than engaging directly with the real thing.
Or then the next level down, where creating amazing work in all of those domains depends on enough "slack" in the system for people to pursue deep work that will not be immediately profitable.
Do you see where I'm going with that? We (and I'm very much including myself: here I am on HN, instead of reading something more substantial) skim the (Wikipedia) surface, instead of diving truly deep. AIs (right now) are the ultimate surface-skimmers, and our fascination with and growing reliance on them reflects something in our current surface-skimming cultural mindset.
I meant it as a simple to understand parallel. Absolutely deep reading and thought is much better than Wikipedia or an LLM chat.
I didn't think you thought otherwise, and apologize if I left that impression. As I said, I spend more time reading Wikipedia articles and watching YouTube videos than I do on any kind of "deep" study, and I think I am less well-equipped for that kind of work than I was twenty years ago. Some of that is life-circumstances - I have a kid, and a more-demanding (time-wise and cognitively) job than I did back then - but some of it is also the ease of access to the shallow stuff, and the instant gratification that it brings. That's cultural, and it's been created (along with, of course, many benefits) of our information revolution. I haven't been inside a library in years.