[dpc_01234]

> We have an in-house, Rust-based proxy server. Claude is unable to contribute to it meaningfully outside

I have a great time using Claude Code in Rust projects, so I know it's not about the language exactly.

My working model is is that since LLM are basically inference/correlation based, the more you deviate from the mainstream corpus of training data, the more confused LLM gets. Because LLM doesn't "understand" anything. But if it was trained on a lot of things kind of like the problem, it can match the patterns just fine, and it can generalize over a lot layers, including programming languages.

Also I've noticed that it can get confused about stupid stuff. E.g. I had two different things named kind of the same in two parts of the codebase, and it would constantly stumble on conflating them. Changing the name in the codebase immediately improved it.

So yeah, we've got another potentially powerful tool that requires understanding how it works under the hood to be useful. Kind of like git.

[lisperforlife]

Recently the v8 rust library changed it from mutable handle scopes to pinned scopes. A fairly simple change that I even put in my CLAUDE.md file. But it still generates methods with HandleScope's and then says... oh I have a different scope and goes on a random walk refactoring completely unrelated parts of the code. All the while Opus 4.5 burns through tokens. Things work great as long as you are testing on the training set. But that said, it is absolutely brilliant with React and Typescript.

[dpc_01234]

Well, it's not like it never happened to me to "burn tokens" with some lifetime issue. :D But yeah, if you're working in Rust on something with sharp edges, LLM will get get hurt. I just don't tend to have these in my projects.

Even more basic failure mode. I told it to convert/copy a bit (1k LOC) of blocking code into a new module and convert to async. It just couldn't do a proper 1:1 logical _copy_. But when I manually `cp <src> <dst>` the file and then told it to convert that to async and fix issues, it did it 100% correct. Because fundamentally it's just non-deterministic pattern generator.

[fullstackchris]

hot take (that shouldn't be?): if your code is super easy to follow as a human, it will be super easy to follow for an LLM. (hint: guess where the training data is coming from!)