I feel like now that LLMs are getting better the quality of the examples matters more than the quantity.
Garbage in, garbage out. If you confuse it with a lot of Junior-level code and have a languages that constantly changes best practices, the output might not be great.
On the other hand, if you have a languages that was carefully designed from the start and avoids making breaking changes, if it has great first party documentation and a unified code style everyone adheres to, the LLM will have an easier time.
The later also happens to be better for humans. Honestly the best bet is to make a good language for humans. Generative AI is still evolving rapidly so no point in designing the lang for current weaknesses.
If the main win of starting over with a new language is that you don't have a giant glut of legacy example code and documentation targeting no-longer-the-best-practice, maybe there's a solution where you take an established modern language like rust or go and feed the LLM a more curated set of material from which to learn.
Like instead of "the entire internet", here's a few hundred best-practice projects, some known up-to-date documentation/tutorials, and a whitelist of 3rd party modules that you're allowed to consider using.