> But LLMs don't care about expressiveness, they care about predictability.

I think this is true, but it misses a very key point. Go does an impressively bad job at designing APIs that are difficult to misuse, so LLMs will misuse them and will require also writing unit tests to walk through it, just to validate it used the libraries correctly. This isn't always possible (or is awkward/cumbersome) for certain scenarios like database querues.

All of the reasons people argue Go is good for LLMs are more true for Rust. You and the LLM can design libraries to be difficult to misuse, and then get instant feedback from the compiler to the LLM about what it did wrong, and often with suggestions about how it should fix them! This also makes RL deriving from compiler feedback more effective.

This allows the LLMs to reason more abstractly at larger scales, since the abstractions are less leaky (unlike in Go). The ceiling on abstraction screws you here, since troubleshooting requires more deep diving. It's the same reason Go projects become difficult for humans at large scales, too.

Go’s much faster compile times are a big advantage over Rust.

Go is not difficult to maintain at large scale, I mean take Kubernetes for example, it's "trivial" to understand and modified even though it's in the millions loc.

Rust is unstable and slow to compile. I think these two features make it bad for LLMs and everything else.

Rust is harder for the bot to get "wrong" in the sense of running-but-does-the-wrong-thing, but it's far less stable than Go and LLMs frequently output Rust that straight up doesn't compile.