I'm not sure that's true. A LLM can code because it is trained on existing code.
Empirically, LLMs work best at coding when doing completely "routine" coding tasks: CRUD apps, React components, etc. Because there's lots of examples of that online.
I'm writing a data-driven query compiler and LLM code assistance fails hard, in both blatant and subtle ways. There just isn't enough training data.
Another argument: if a LLM could function like a senior dev, it could learn to program in new programming languages given the language's syntax, docs and API. In practice they cannot. It doesn't matter what you put into the context, LLMs just seem incapable of writing in niche languages.
Which to me says that, at least for now, their capabilities are based more on pattern identification and repetition than they are on reasoning.
Have you tried new languages or niche languages with claude sonnet 3.5? I think if you give it docs with enough examples, it might do ok. Examples are crucial. I’ve seen it do well with CLI flags and arguments when given docs, which is a somewhat similar challenge.
That said, you’re right of course that it will do better when there’s more training data.
Empirically, LLMs work best at coding when doing completely "routine" coding tasks: CRUD apps, React components, etc. Because there's lots of examples of that online.
I'm writing a data-driven query compiler and LLM code assistance fails hard, in both blatant and subtle ways. There just isn't enough training data.
Another argument: if a LLM could function like a senior dev, it could learn to program in new programming languages given the language's syntax, docs and API. In practice they cannot. It doesn't matter what you put into the context, LLMs just seem incapable of writing in niche languages.
Which to me says that, at least for now, their capabilities are based more on pattern identification and repetition than they are on reasoning.