zlacker

>>tehnub+(OP)
I'm biased by my preferred style of programming languages but I think that pure statically typed functional languages are incredibly well suited for LLMs. The purity gives you referential transparency and static analysis powers that the LLM can leverage to stay correctly on task.

The high level declarative nature and type driven development style of languages like Haskell also make it really easy for an experienced developer to review and validate the output of the LLM.

Early on in the GPT era I had really bad experiences generating Haskell code with LLMs but I think that the combination of improved models, increased context size, and agentic tooling has allowed LLMs to really take advantage of functional programming.

>>solomo+sk
I'm inclined to agree with you in principle, but there's much, much less Haskell examples in their training corpus than for JavaScript or Python.

>>eru+bl
For the little Haskell I've done with llms, I can tell you they're not bad at it.

Actually, Haskell was a bit too hard for me on my own for real projects. Now with AI assistants, I think it could be a great pick.