I haven’t had an issue using Python with LLMs where I have to decide “Should one use pip, poetry, or uv?” Since there is enough training data using pip or just choose that since it is the most boring solution and many of the commands map to uv since uv has a superset of features. Not that go is a bad solution honestly I would just say use what you know best.
> From a model’s standpoint, there are simply too many ways to write any of this<p>They seem quite good at figuring this out in my experience
Has Go become a "boring language"?
Contradictory anecdote: there’s basically only one way to write Elm, as it is a very trend-resistant language with minimal updates over long timespans, but most agents in my experience will throw Haskell syntax and Prelude functions into their Elm output. Compiler or LSP will often set them right but they still try it initially
Interesting, what models are you using? My use with sonnet 4.6 has been a breeze for the most part
Interesting, I have a different experience.<p>I have worked extending the Elm compiler and both Opus 4.6, GPT 5.4 and GLM 5 had no issues both with the Elm compiler (written in Haskell) and my extended Elm.<p>I didn't see them hallucinate much, not more than on mainstream languages.