It seems self-evident it will, and it's largely self-reinforcing.

Less documentation/examples of new tech -> New model doesn't have enough info on new tech to be useful -> Less uptake of new technology -> Less documentation/examples to build a corpus....

I do wonder if this problem could get solved by basically providing documentation explicitly written for LLMs to consume and produce more detailed "synthetic" documentation/examples from. No idea if that's possible or even wise, but probably a problem space worth exploring. Or if these LLMs develop some sort of standardized way to rapidly apply new bodies of work that avoids costly retraining - like kernel modules, but for LLMs.