alt Hacker NewsI wish more had been written about the first assertion that using an LLM to code is like gambling and you're always hoping that just one more prompt will get you what you want.
It really captures how little control one has over the process, while simultaneously having the illusion of control.
I don't really believe that code is being made verbose to make more profits. There's probably some element of model providers not prioritizing concise code, but if conciseness while maintaining "quality" was possible is would give one model a sufficient edge over others that I suspect providers would do it.
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But just like gambling, there are ways to do it correctly.
Yes, there are the grandmas in a trance vibe-gambling by shoving a bucket of quarters in a slot machine.
But you also have people playing Blackjack and beating the averages by knowing how it's played, maybe having a "feel" for the deck (or counting cards...), and most importantly knowing when to fold and walk away.
Same with LLMs, you need to understand context sizes and prompts and you need to have a feel for when the model is just chasing its own tail or trying to force a "solution" just to please the user.
> It really captures how little control one has over the process, while simultaneously having the illusion of control.
This is actually a big insight about life, that in some eastern philosophies, you are supposed to arrive to
We love the illusion of control, even though we don’t really have it. Life mostly just unfolds as we experience it
Something I caught about Andrej Karpathy’s original tweet, was he said “give into the vibes”, and I wonder if he meant that about outcomes too.
Agreed, I've been thinking about the first assertion a lot recently as I've been using Cursor to create a react app. I think it's more prevalent in frontend development because it tightens the feedback loop considerably, and the more positive feedback you get, the more conditioned you get to reach for it anytime you need to do anything in code.
I think there's another perverse incentive here - organisations want to produce features/products fast, which LLMs help with, but it comes at the cost of reduced cognitive capabilities/skills in the developers over the longer term as they've given that up through lack of use/practice.