I've been guilty of this and gotten pushback from my manager: "this feels like homework, cut these options down to 100 words each, max".
Curation and refinement are even more important when you can have genAI generate reams of text.
Seeking outside signals is even more important, like talking to customers, looking at real usage data, and more. It's too easy to trust believe what Claude tells you, even if you say "please argue against this idea", which you always should.
It matches the pattern of LLMs being very good at simulating the form of work output, which is an issue with code but it seems quite exacerbated with anything non-verifiable, like written communication.
I'm using Claude to write large files too, but it's a very iterative process and involves a lot of reading and correcting.
to be fair, i've been guilty of this with code. Ask claude to generate a python script that takes X as input and produces Y as output, run it, pipe to more, output looks ok but i don't check everything, write it to a file, send it on.