On generative AI for programming Rust

October 2024

You can tell how fast this space and opinions were moving because it took me a few conversations over a few weeks to unhold this.

This was originally posted as a comment on r/rust, but I felt like it belonged here too.

Question: I think [AI tools] can be helpful and save developer time when used correctly, but you cannot trust them to generate correct code. That’s why strong type systems (like Rust’s) are still very important for checking program correctness (combined with unit tests etc.).

My comment:

(Disclaimer: I have free Github Copilot via the OSS maintainer program)

I agree that compared to a JavaScript codebase, Rust does help catch the most egregious AI mistakes. However, what I’ve found is that AI codegen is often either subtly wrong in the nitty gritty logic (makes sense, it can’t reason), or correct in mechanistic execution but wrong in approach (say I wanted an implementation that did the least amount of expensive copies, and the AI codegen’d something that Arc’d everything).

I find that the older dumber AI models were in fact more productive, in that they were more like pattern-replicating tools (give it an example impl and a list of types and it will generate an impl per type with the correct substitutions, even if there’s differing cases and plurals/singulars transforms to do, which editor macros have difficulty with, or would take comparitively too long).

As a result I’ve gone from “ignore suggestions 95% of the time” to “disable copilot globally and enable it for singular tasks.” I find that I have a renewed productivity and heightened enjoyment of solving problems; that indeed Copilot, even if I ignored its solutions, would influence my direction. While initially it feels like a productivity upgrade, in the end it’s like slogging against the machine, trying to make it do what I want.

I very much feel like I’m in a science fiction novel of the last millenium in saying that, but using AI codegen or chat is handing off your thought process to a computer and being in this forever fog of frustration and feeling wrong but surely you can’t unplug, for unplugging would be coming back to the last great age where we still banged rocks together.

I find that I improve my craft less or not at all when using AI codegen, because I’m not using my brain to solve problems from scratch.

I am moderately worried — moderately because I don’t have good data on it — that this whole experiment is going to spell disaster for knowledge industries. I am by no means a beginner. In fact I find that I am in some ways so far removed from the experience of learning Rust basics that I completely fail at teaching it, which not a humble brag but rather a distressing realisation. If I feel like using AI is preventing me to effectively keep improving myself, then what happens to someone who spent their entire programming life with AI?

Yet I see a lot of beginners who say they’re helped by AI, especially AI chat, because they’re able to ask questions and have instant answers. Those might be wrong to an extent, but so might a human mentor. I don’t really know what to feel here. I am no longer at a stage where talking to a chatbot genuinely helps me solve problems, because the problems I have cannot be answered by a language model. They require reason and empathy. And yes, I am talking of software development problems. So I can’t relate to this need, but that doesn’t mean it doesn’t exist.

I find it profoundly sad that Stack Overflow and related sites now have a reputation, deserved or not, for being hostile and unapproachable. I do believe that, compared to inscrutable Discords, interminable GitHub Issues threads, disorganised wikis, or unfocused forum and reddit and social posts, the Stack Overflow Q&A model was (in 2010-2015 at least) the best at providing short and long term resources in a fairly lightweight community-building format. The rules made it hard for newbies, but they cannot be removed, for it is the rules that force you to learn how to ask a question. To learn to think through your problem. There were many times when I found my solution while writing a question; a kind of rubber duck but into a textbox.

The problem I have with chat AI is that it doesn’t know how to say “I don’t know.” It is the ultimate rubber duck programming tool, but where a rubber duck can’t answer if you yourself cannot solve your own problem, and where a well-run Q&A site will eventually find the right answer (and the right person to answer the question), chat AI will confidently invent utter bullshit. And it will do so in a way that is indistinguishable from when it gives the correct answer. And it might, at random, answer simple questions wrong because it got tripped up by an irrelevant word.

Another thing I find is that colleagues at work spend time asking Claude the same question again and again. They’ll do prompt engineering for fifteen minutes if they’re not satisfied, instead of going “ah well, let me just think for three minutes instead of getting an instant answer.” They’ll eschew more precise tools, including their own mind, for the all-doing box of averages.

So yes, I think that Rust gives you a marginal advantage against say, JS or PHP or C when using it with AI. But while I do use Copilot for specific pattern-replicating tasks, where it excels, I think it is a net negative to use for general purpose programming, regardless of language.

Of course, your experience may vary.