In a (possibly near) future where most new code is generated by AI bots, the code itself becomes incidental/commodotized and it's nothing more than an intermediate representation (IR) of whatever solution it was prompt-engineered to produce. The value will come from the proposals, reviews, and specifications that caused that code to be produced.
Github is still code-centric with issues and discussions being auxilliary/supporting features around the code. At some point those will become the frontline features, and the code will become secondary.
This is exactly what people said about the "low code revolution".
Not saying that you are wrong, necessarily. But I think it's still a pretty broad presumption.
I'm definitely not an AI skeptic and I use it constantly for coding, but I don't think we are approaching this future at all without a new technological revolution.
Specifications accurate enough to describe the exact behaviors are basically equivalent to code, also in terms of length, so you basically just change language (and current LLM tech is not on course to be able to handle such big specifications)
Higher level specifications (the ones that make sense) leave some details and assumption to the implementation, so you can not safely ignore the implementation itself and you cannot recreate it easily (each LLM build could change the details and the little assumptions)
So yeah, while I agree that documentation and specifications are more and more important in the AI world, I don't see the path to the conclusions you are drawing