Comment by wccrawford

I'm seeing people who _used to be_ like that losing that understanding without realizing it's happening - they have a superficial idea of what the code is doing, enough to feel like they understand it, but the change is apparent when watching them handle something unexpected.

> I don't think it's generalizable. The kind of person who copy and pastes from the AI is the kind who did the same from StackOverflow before. It's more compelling, and we probably see more of them because of it, but it's the same general thing.

There's an infinity between someone who has to panel beat what they copied off SO and someone who just bangs their head repeatedly against an LLM.

In essence, you are correct. What I see with LLMs is how they will happily make up stuff, meanwhile you can pretty much exhaust SO, until you are forced to understand the problem you are having.

You don't have to be a certain person to fall into this trap, you just condition your brain to accept this workflow somewhere.

Pair this with day to day work stress like time and amount of tasks and you almost give in to a sort of addiction to deal with it all.

> The kind of person who copy and pastes from the AI is the kind who did the same from StackOverflow before. The kind of person who insists on understanding things and working through the problem has always been rarer.

Well, this is where I disagree. I have coworkers who used to insist on understanding and now are doing exactly as OP wrote - copy/pasting from the LLM to brute force error messages. I don't know if it's generalizable but this is what I see in <big tech> working on a frontend team with mid to senior level engineers who I respect.

One example a few weeks ago, I was helping a coworker root cause a bug in a React codebase. Pair programming isn't necessarily common but sometimes you see someone banging their head at a problem and you get curious. It turned out there was an effect (a callback that's invoked whenever some state changes) that invokes an API and this effect caused an infinite render loop because the error handling wasn't written correctly. It was something silly like - Call this API if we have no data -> get error -> update state -> call API again because we have no data...

That was almost immediately what I suspected but my colleague was pulling out all the stops usually reserved for when you're desperate or need a sanity check, like logging to stdout after each line. Both my colleague and the LLM were convinced the problem lied in the pagination logic of the helper that invokes the API. He ended up rewriting that helper imperatively and functionally. To his credit, he rewrote it by hand and implemented the recursion correctly but he was baffled when the problem remained. Completely surprised Pikachu face.

I don't think my coworker changed or suddenly stopped caring. It seems much more likely this is a predictable outcome when you lean heavily into AI authoring code for a sustained period of time. I'd also say that in itself is a consequence of the extreme pressure being exerted across the entire company to ship more code and review more code, faster.

The difference between the two is that friction is learning.

the less friction the less growth.

So even if they copied from SO they would have better knowledge than an Ai user.

This isn’t speculation either, theres an MIT study which this is based on. https://www.media.mit.edu/publications/your-brain-on-chatgpt...