Yes but it goes deeper than just corpus, because not all programming languages are created equal. More statically enforced language perform better with AI because the tooling catches more bugs earlier. Highly dynamic languages like JS are very poor rewrite targets, despite being popular, because you essentially have to live in the debugger and employ maximum TDD to make it work reliably. And AI doesn't do that.

Consider just having a typechecker. That alone eliminates a whole class of bugs and unit tests, which means your remaining unit tests check more logic. I've seen JS projects with high test coverage that cover essentially zero logic, only type checking class things. And nobody even knows it, really. But when your tests are just "okay pass an empty array. Now an empty string. This should fail, great. Now pass an array with the wrong elements..." you're not testing anything. You're probing the type system, which many languages do automatically and perfectly.

Meta for example is spending a lot of effort and money into creating new curated programming training sets.

That means at least from their POV what's already available is not enough or not good enough, and if they're correct then the companies making the models can "artificially" inflate a language's representation.

I never said it did.

My comment shouldn't be read as an explanation for why Anthropic chose Rust in this case.

I was simply disputing the claim that LLMs are good at all languages, and that their biases--both intentional and otherwise--will swing the entire industry.