Aside from the obvious problem that there's not enough FP in the training corpus, it seems like terser languages don't work all that well with LLMs.
My guess is that verbosity actually helps the generation self-correct... if it predicts some "bad" tokens it can pivot more easily and still produce working code.
I’d believe that, but I haven’t tried enough yet. It seems to be doing quite well with jq. I wonder how its APL fares.
When Claude generates Haskell code, I constantly want to reduce it. Doing that is a very mechanical process; I wonder if giving an agent a linter would give better results than overloading it all to the LLM.
The power of Haskell in this case is the fearless refactoring the strong type system enables. So even if the code generated is not beautiful, it can sit there and do a job until the surrounding parts have taken shape, and then be refactored into something nice when I have a moment to spare.