I liked Rust before running a benchmark, but the gap between how effectively most LLMs write in Rust vs Go was still surprisingly large to me (especially in agentic harnesses where they can fix the initial environment issues). I've become a pretty big Rust evangelist after seeing that. We've had a lot of success writing batch processing tools in Rust to be called by our existing codebase, but haven't attempted a full production migration... yet.

I will say that many of the issues with Go in the article, especially re: nil handling are increasingly solved by thorough coding reviews with Codex. Better to not have the issue in the first place, sure, but these kinds of security bugs are becoming optional to developers who put in at least as much effort to review and understand code as they put into the initial design and execution.

Language data at https://gertlabs.com/rankings?mode=agentic_coding

The detailed compiler errors and strong type system makes the change -> compile -> change loop simple for agents to handle. Rust provides very strong rails it forces users on to. Codex always manages to get something to compile.

The downside is that maybe it should fail sometimes when an idiomatic approach isn’t viable… instead it will implement something stupid that compiles and meets the request.

The weakness of Rust WRT LLMs is compilation times. LLMs code faster and hence spend relatively more time waiting for compilation than humans do, so on reasonably sized projects (e.g. 100k+ lines) Rust's ~10x slower compilation starts showing up as a bottleneck. If you're writing some critical infrastructure it makes sense to pay that cost, but if you're writing some internal service that's not publicly exposed to the internet then development velocity may be a bigger concern. (I'd argue that slow compilation also influences human development velocity, but for some reason developers very rarely try to quantify this.)