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LLMs have been solid at writing Common Lisp since Sonnet 3.5 and have been near flawless since the Opus 4.5 release. The niche language thing is really not a p
by wild_egg 26d ago
LLMs have been solid at writing Common Lisp since Sonnet 3.5 and have been near flawless since the Opus 4.5 release.
The niche language thing is really not a problem at all any more. If you're working in some esolang it doesn't take more than a 1-2k token primer in the context to get great results, and lisp is popular enough to not even need that.
The benefit of having the agent directly in the image like with Autolith here is that it can directly inspect all defined symbols and explore and orient itself automatically. Really doesn't need much guidance to get great results.
- magnusi 25d ago(author of autolith here) This all correct, I'd also add that in my experience, the GPTs are even better at Lisp, namely in the counting parentheses department. Which is not an issue that much per-se because in Autolith, the harness detects Lisp file edits (CL, Scheme, Clojure) and gives hints when the edits lead to unbalanced files (The heuristic is pretty simple, we detect if there's a mismatch, and if yes, it provide hints where the extra/missing might be based on indentation)
- a2ff6eeb0 25d agoBut LLMs already do that with text, don't they? And I don't really want to interact with the code directly, so I'm not sure why I should care what language is used other than raw performance and LLMs ability to use it. Do you have benchmarks on non-trivial tasks (say, generating zstd) that show it does any better than rust?