This is one of my major concerns about people trying to use these tools for 'efficiency'. The only plausible value in somebody writing a huge report and somebody else reading it is information transfer. LLM's are notoriously bad at this. The noise to signal ratio is unacceptably high, and you will be worse off reading the summary than if you skimmed the first and last pages. In fact, you will be worse off than if you did nothing at all.

Using AI to output noise and learn nothing at breakneck speeds is worse than simply looking out the window, because you now have a false sense of security about your understanding of the material.

Relatedly, I think people get the sense that 'getting better at prompting' is purely a one-way issue of training the robot to give better outputs. But you are also training yourself to only ask the sorts of questions that it can answer well. Those questions that it will no longer occur to you to ask (not just of the robot, but of yourself) might be the most pertinent ones!

So what we now have is a very expensive and energy-intensive method for inflating data in a lossy manner. Incredible.

This reminds me of that "telephone" kids game.

https://en.wikipedia.org/wiki/Telephone_game

So a circular economy in which you add mistakes

For all the technology we develop, we rarely invest in processes. Once in a blue moon some country decides to revamp its bureaucracy, when it should really be a continuous effort (in the private sector too).

OTOH, what happens continuously is that technology is used to automate bureaucracy and even allows it to grow some complexity.

An economy of the LLMs, by the LLMs, for the LLMs, shall not perish from the Earth.

See, this is an opportunity. Company provides AI tool, monitors for cases where AI output is being fed as AI input. In such cases, flag the entire process for elimination.