Comment by daxfohl
5 hours ago
I worry about the "brain atrophy" part, as I've felt this too. And not just atrophy, but even moreso I think it's evolving into "complacency".
Like there have been multiple times now where I wanted the code to look a certain way, but it kept pulling back to the way it wanted to do things. Like if I had stated certain design goals recently it would adhere to them, but after a few iterations it would forget again and go back to its original approach, or mix the two, or whatever. Eventually it was easier just to quit fighting it and let it do things the way it wanted.
What I've seen is that after the initial dopamine rush of being able to do things that would have taken much longer manually, a few iterations of this kind of interaction has slowly led to a disillusionment of the whole project, as AI keeps pushing it in a direction I didn't want.
I think this is especially true if you're trying to experiment with new approaches to things. LLMs are, by definition, biased by what was in their training data. You can shock them out of it momentarily, whish is awesome for a few rounds, but over time the gravitational pull of what's already in their latent space becomes inescapable. (I picture it as working like a giant Sierpinski triangle).
I want to say the end result is very akin to doom scrolling. Doom tabbing? It's like, yeah I could be more creative with just a tad more effort, but the AI is already running and the bar to seeing what the AI will do next is so low, so....
It's not just brain atrophy, I think. I think part of it is that we're actively making a tradeoff to focus on learning how to use the model rather than learning how to use our own brains and work with each other.
This would be fine if not for one thing: the meta-skill of learning to use the LLM depreciates too. Today's LLM is gonna go away someday, the way you have to use it will change. You will be on a forever treadmill, always learning the vagaries of using the new shiny model (and paying for the privilege!)
I'm not going to make myself dependent, let myself atrophy, run on a treadmill forever, for something I happen to rent and can't keep. If I wanted a cheap high that I didn't mind being dependent on, there's more fun ones out there.
Businesses too. For two years it's been "throw everything into AI." But now that shit is getting real, are they really feeling so coy about letting AI run ahead of their engineering team's ability to manage it? How long will it be until we start seeing outages that just don't get resolved because the engineers have lost the plot?
I think I should write more about but I have been feeling very similar. I've been recently exploring using claude code/codex recently as the "default", so I've decided to implement a side project.
My gripe with AI tools in the past is that the kind of work I do is large and complex and with previous models it just wasn't efficient to either provide enough context or deal with context rot when working on a large application - especially when that application doesn't have a million examples online.
I've been trying to implement a multiplayer game with server authoritative networking in Rust with Bevy. I specifically chose Bevy as the latest version was after Claude's cut off, it had a number of breaking changes, and there aren't a lot of deep examples online.
Overall it's going well, but one downside is that I don't really understand the code "in my bones". If you told me tomorrow that I had optimize latency or if there was a 1 in 100 edge case, not only would I not know where to look, I don't think I could tell you how the game engine works.
In the past, I could not have ever gotten this far without really understanding my tools. Today, I have a semi functional game and, truth be told, I don't even know what an ECS is and what advantages it provides. I really consider this a huge problem: if I had to maintain this in production, if there was a SEV0 bug, am I confident enough I could fix it? Or am I confident the model could figure it out? Or is the model good enough that it could scan the entire code base and intuit a solution? One of these three questions have to be answered or else brain atrophy is a real risk.
My disillusionment comes from the feeling I am just cosplaying my job. There is nothing to distinguish one cosplayer from another. I am just doordashing software, at this point, and I'm not in control.
> Like if I had stated certain design goals recently it would adhere to them, but after a few iterations it would forget again and go back to its original approach, or mix the two, or whatever.
Context management, proper prompting and clear instructions, proper documentation are still relevant.
I've been thinking along these lines. LLMs seem to have arrived right when we were all getting addicted to reels/tic tocks/whatever. For some reason we love to swipe, swipe, swipe, until we get something funny/interesting/shocking, that gives us a short-lasting dopamine hit (or whatever chemicals it is) that feels good for about 1 second, and we want MORE, so we keep swiping.
Using an LLM is almost exactly the same. You get the occasional, "wow! I've never seen it do that before!" moments (whether that thing it just did was even useful or not), get a short hit of feel goods, and then we keep using it trying to get another hit. It keeps providing them at just the right intervals for people to keep them going just like they do with tick tock
My experience is the opposite - I haven't used my brain more in a while.. Typing characters was never what developers were valued for anyway. The joy of building is back too.
Same. I feel I need to be way more into the domain and what the user is trying to do than ever before.
> I want to say it's very akin to doom scrolling. Doom tabbing? It's like, yeah I could be more creative with just a tad more effort, but the AI is already running and the bar to seeing what the AI will do next is so low, so....
Yea exactly, Like we are just waiting so that it gets completed and after it gets completed then what? We ask it to do new things again.
Just as how if we are doom scrolling, we watch something for a minute then scroll down and watch something new again.
The whole notion of progress feels completely fake with this. Somehow I guess I was in a bubble of time where I had always end up using AI in web browsers (just as when chatgpt 3 came) and my workflow didn't change because it was free but recently changed it when some new free services dropped.
"Doom-tabbing" or complete out of the loop AI agentic programming just feels really weird to me sucking the joy & I wouldn't even consider myself a guy particular interested in writing code as I had been using AI to write code for a long time.
I think the problem for me was that I always considered myself a computer tinker before coder. So when AI came for coding, my tinkering skills were given a boost (I could make projects of curiosity I couldn't earlier) but now with AI agents in this autonomous esque way, it has come for my tinkering & I do feel replaced or just feel like my ability of tinkering and my interests and my knowledge and my experience is just not taken up into account if AI agent will write the whole code in multi file structure, run commands and then deploy it straight to a website.
I mean my point is tinkering was an active hobby, now its becoming a passive hobby, doom-tinkering? I feel like I have caught up on the feeling a bit earlier with just vibe from my heart but is it just me who feels this or?
What could be a name for what I feel?
LLMs have some terrible patterns, don't know what do ? Just chuck a class named Service in.
Have to really look out for the crap.
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