It's as popular as you make it. Nothing is stopping you from using it. People generate code for what they are familiar with or have desire for. There are people who have wanted to give rust a try and AI opens that possibility up. There are certainly less people that want to try Haskell. Furthermore, Rust has more training data so LLMs generally will provide better Rust code than Haskell code. Because of LLM, I'm back into obscure languages that I didn't have the mental capacity to carry day by day. Prolog, Lisp and Forth, and like you said, they are very terse and token efficient. However, I must point out that terse was only relevant prior to the entire thinking era, a model could use 100k tokens to think only to give you 100 tokens of final output.

I've been generating probably 500k lines of Rust with all the SOTA models (and now DeepSeek). Every model does an absolutely horrible job generating good Rust code. You have to babysit it and you need to question everything the model spat out.

I mean, free functions and no general nice trait/struct/enum based architecture, random `Mutex`/`RwLock` everywhere, all your big futures inside a `tokio::select!` etc.

Yes it's great when you do your first Rust project. After a year it's a nightmare if you don't keep a clear control how the code is generated and organized.