So I've been working on a project in Rust because a library that's appropriate for the design has a terrific Rust API and a miserable C API. I've been loosely tracking Rust since before 1.0 and I've never felt it's a language that's easy to be productive in, and not just because of lifetimes and the borrow checker. So I've been using coding agents to get me through. The problem is I don't have a sense of what feels good or bad, so I can't direct the AI to steer in another direction. And neither does AI it turns out. So I'm still going really really slow. AI is still not a substitute for lack of experience or knowledge.

The best thing I can compare it to is Adderall (without a prescribed reason for taking it). Have you ever been reading a dense text and realized halfway through the page that you didn't comprehend anything? I get this kinda sick feeling in my stomach and then I back up to the last point I was really paying attention. Adderall gets rid of that feeling, and I can just read through. But am I actually comprehending the text or is the drug just raising the ambient dopamine levels enough that I'm not feeling the missed comprehension? Using coding agents makes me feel the same way. I'm not feeling the struggle of learning something new, but I worry I'm writing code no one will be able to fix, even the AI.

Anyways, I've defaulted to using a free chatbot "ChatGPT style". It makes a lot of mistakes and forces me to go through everything over and over.

I wonder how people can like LLM generated code so much and then at the same time find LLM generated prose so repulsive. Is the quality of LLM generated code higher? I would think there’s much more prose than code to train on. Or is it that we don’t care about that as we’re only looking at the effects of that code? Maybe people pick Rust as they won’t understand what the LLM writes anyway so there’s less guilt about writing bad code. Same for me if I would read Assembly, I guess I can make out what it does mostly but I couldn’t judge its quality really. But it doesn’t matter to me as I never read it anyway and I never go down to that level of abstraction anymore. That’s what’s happening here I think with people picking Rust for LLM coding, they don’t care about the code because they can’t really read it anyway and they never go down to its level of abstraction for debugging anymore, only the few specialists working on the foundations do that.

I still think LLMs generate boilerplate and examples that should have been in the docs to begin with. We never really needed LLMs. We needed more active communities and maintainers to care about the "boring" parts.

All the rest of the generated code is usually slop. It only gets worse the further away you get from the most popular idioms that have already been written.

I don't think we're ever getting beyond that point with statistical "AI".

It's actually a pretty significant defeat for any open source tools that wanted to maintain control over what is considered canonically good. Maintainers are now forced to be a lot more defensive about what is possible with their tools. This limits their scope and kills curiosity and creativity.

We're lucky that all this happened after we found enough stability that people aren't too interested in creating new languages and frameworks from scratch like it was a decade ago.

> one thing is pretty clear: the act of familiarizing yourself with a language no longer matters and some of the friction that mattered for humans does not matter for agents.

sure, man, whatever.

Yet another HN item linking to a blog post by someone extolling the brave new world we are in due to LLM-generated code. Reminds me of this:

https://www.youtube.com/watch?v=JeNS1ZNHQs8

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