The "cognitive debt" result has prior art that reads it as role confusion, not neurology

Rao's essay responds to the Your brain on ChatGPT preprint, the EEG study in which undergraduates leaning on GPT-4o showed weaker alpha-beta coupling, produced similar prose, and later could not quote their own sentences. He accepts the data and rejects the interpretation. His claim, stated as a principle:

"For today's text generators, the cognitive effects of prompting an LLM are empirically indistinguishable from supervising a junior human."

On that reading the flat neural traces are the signature of supervisory control, the delegate, monitor, integrate, ship loop that professors run with grad students and editors with freelancers, and the students failed because "freshman comp doesn't teach management." He calls them accidental managers, and prescribes delegation protocols, quality gates and exception handling rather than abstinence. He also relocates the risk he does take seriously, away from the brain: an "index-fund pull toward the linguistic mean, cheap, reliable, originality-suppressing."

The essay is self-disclosed AI-assisted work: it publishes its own recipe and links the model transcript that produced it, and at least one commenter disputes whose argument it is on that basis. It is also fourteen months old. It is here because the argument now running about whether agents dull the people supervising them is being had largely without it.

Why it matters: If prompting is supervision, then the things worth measuring are the supervisor's, not the model's: how fast errors are caught, what the quality gate actually gates, what the exception path is when the agent returns something plausible and wrong. That is the same list a harness has to implement, and it suggests the skill gap in agent-assisted work is a management gap with a long literature rather than a new deficit.