The Rust ecosystem is also a moving target.
Virtually all crates are still at version 0.x and introduce constant breaking changes: [https://00f.net/2025/10/17/state-of-the-rust-ecosystem/](https://00f.net/2025/10/17/state-of-the-rust-ecosystem/)
If you don’t want to use obsolete versions of dependencies, you need to explicitly tell the model that. Then you have to hope it can adopt new APIs it wasn’t trained on, rewrite existing code to handle the breaking changes, and keep your fingers crossed that nothing else breaks in the process.
LLMs perform much better with Go, not only because of the lack of hidden control flow (LLMs can deal with that, but it costs a lot of tokens) but mainly because both the language and its dependencies introduce very few breaking changes.
This hasn’t been true for some months. Claude has gotten better about adding latest versions of crates, and when it does encounter a breaking change from what it expects it is usually very quick about finding the change in the docs or crate source code.
What you are talking about used to be a pain point, but is now pretty much gone.
Rust can be a real superpower for AI-assisted dev work, because the compiler outputs very good errors, and the type system catches most safety bugs.