In a lot of my AI assisted writing, the prompt is an order of magnitude larger than the output.
Prompt: here are 5 websites, 3 articles I wrote, 7 semi-relevant markdown notes, the invitation for the lecture I'm giving, a description of the intended audience, and my personal plan and outline.
Output: draft of a lecture
And then the review, the iteration, feedback loops.
The result is thoroughly a collaboration between me and AI. I am confident that this is getting me past writer blocks, and is helping me build better arcs in my writing and lectures.
The result is also thoroughly what I want to say. If I'm unhappy with parts, then I add more input material, iterate further.
I assure you that I spend hours preparing a 10_min pitch. With AI.
I can only say that at family meetings, I hear people talk about contracting with a shop that used to have 4 web designers, but now it's 1 guy, delivering 4x faster than before.
Uhm, no?
Even with "simple" examples like Dijkstra's shortest path, the spec is easier than the implementation. Maybe not for you, but try it out on an arbitrary 5-yr old.
On the extreme end, you have results in maths, like Fermat's Last Theorem. Every teenager can understand the statement (certainly after 10 mins of explanation) but the proof is thousands of pages of super-specialized maths.
It is a spectrum. For cryptography, compression, error-correction, databases, etc, the spec is often much simpler than the implementation.
I talk to other people. They influence me, steer me. I am okay with that.