[tern]

Rust, Elixir, and Go are the way to go for LLMs in my testing and experience, for this and other reasons

[cpursley]

Here’s some of the reasons it’s so good with Elixir:

https://dashbit.co/blog/why-elixir-best-language-for-ai

[tern]

My intuitions for using Elixir:

- Durable, 'enterprise grade' software patterns are baked into the runtime and into common, stable libraries that everyone uses

- You can use Ash, which pretty much entirely solves architectural considerations for many types of backends

- The tooling for inspecting and enforcing style (tidewave, credo, dialyzer, Dan's "vibe" ecosystem tools) is far beyond what I see in other ecosystems

- Ecosystem coverage for pretty much everything you need, including numerical software

- Excellent performance escape hatches (NIFs)

And, as has been shown in various benchmarks, agents are quite good at it.

My one problem in practice has been that getting tests right is hard. LLMs need a lot of cajoling to not build flaky tests with all the concurrency, and I find myself spending hours rewriting parts of the test suite once or twice a week.

[cpursley]

Is ex_slop one of Dans? That one is great. Been looking for an equivalent in Swift.

[mohamedkoubaa]

I have no professional experience in Rust and over 10 years in c++ but to me the decision to use rust in a greenfield project written by agents was obvious.