Hard disagree. The best language for AI is one that has strong compiler soundness (ie type system) that can reject incorrectness and provide feedback as to correctness to refactors. One can substitute with property based tests but it won’t be as good as soundness + pbt. Speaking from experience here… https://ghuntley.com/oh-fuck && https://ghuntley.com/stdlib
I do however agree that there’s langs that are not as suitable for LLMs (Java) due to their verbosity (and engineers sort classes onto filesystem like a filing drawer. LLMs work best when everything for a domain, including tests, is in a single file).
Increased verbosity of the grammar does yield token wastage/ineffectiveness.
Having said all that - compile time matters HEAPS. The faster you can optimise your compile time the more loops (throwing pancakes at the wall) you can do. Here’s where it gets crazy though, one can loop a verbose compilation w/metrics back into the LLM and ask the LLM to propose improvements on how to make the compile faster. It works…
I do however agree that there’s langs that are not as suitable for LLMs (Java) due to their verbosity (and engineers sort classes onto filesystem like a filing drawer. LLMs work best when everything for a domain, including tests, is in a single file).
Increased verbosity of the grammar does yield token wastage/ineffectiveness.
Having said all that - compile time matters HEAPS. The faster you can optimise your compile time the more loops (throwing pancakes at the wall) you can do. Here’s where it gets crazy though, one can loop a verbose compilation w/metrics back into the LLM and ask the LLM to propose improvements on how to make the compile faster. It works…