you're talking about specifically using genetic programming to create new programs as opposed to gradient decend in LLMs to minimize a loss function, right?

How would you construct a genetic algorithm to produce natural language like LLMs do?

Forgive me if i'm misunderstanding, but in programming we have "tokens" which are minimal meaningful bits of code.

For natural languages it's harder. "Words" are not super meaningful on their own, i don't think. (at least not as much as a token) so how would you break down natural language for a genetic algorithm?