Sadly not my experience. When I give this kind of feedback on a document, highlight a gap, or give constructive feedback, most of the time this feedback is fed back to the AI and a new revision of the document shows up.

BUT because it is AI it's not that section that's addressed, it's about 90% of the document that now has changed, and I need to spend another gargantuan effort to review it. It's like by trying to be helpful I actually lose more time.

The AI has made it so that the thinking before writing is mostly gone, and shifted that step to the reviewers.

Sounds like Claude. I haven’t made this experience with the large OpenAI models.

Left this way, every collaboration can turn into what used to be the worst nightmare type with that one unavoidable stakeholder or coauthor who likes to procrastinate and then create an insane fire drill in the final moments before a deadline.

Now, no matter the amount of preparation work, those last rounds can completely rewrite something with no hope of review. No iterative improvement. No ratcheting towards a known quality. Just a bunch of cargo cult review followed by YOLO-style, vibe-everything absurdity.

Review burden is increasingly higher for many people, with Tech likely being patient 0 for the rest of the economy.

The ratio of verification capacity to generation capacity, V/G, has broken with LLMs. It’s not simply an issue of more generation or less review.

The impression seems to be that individuals are more productive, but that productivity is someone else’s review burden. So the team/firm as a whole is not better off.

The cheap generation of content does mean that reviewer capacity is now a limited resource.

Unless your firm is aware and is measuring time spent on reviewing slop, there is no incentive or structure to ensure that time is respected and valued.

This is a management and awareness problem since the typical response is “use a bot to review it.”