Relocating Trust to the Verifier A Truth-Maintenance System for an AI-Generated Theory of Everything

A fluent, always-available, approval-seeking generative model, pointed at an open-ended

foundational-physics task by a human who wants it to succeed, forms a mutual-confirmation

loop with no reality-check on either side. Theories of everything are the maximally dangerous

case: the claims are grand, the mathematics can be made internally consistent, and the only

decisive check — experiment — is decades away or absent, so the domain strips out the cheap

reality-checks that catch confabulation elsewhere. We argue the cure is not a better model

but a structural one: relocate trust from the generator to a verifier. We present ptms,

a truth-maintenance system that enforces consistency, not truth, treating every AI-supplied

justification as untrusted until it binds to checkable evidence — a cited script that exits 0,

a retired claim’s signature flagged at every surviving site, a cross-reference that resolves.

We report its design and its behaviour on a real six-month AI-assisted theory-of-everything

corpus (∼250 canonical claims,∼120 self-asserting scripts), where it mechanically catches

named failure classes: un-propagated retractions, evidence regressions, seductive numerical

coincidences, and live claims standing on retracted foundations. We are explicit about the

limit: the system makes such research auditable and constrained, not correct — only forward

prediction closes the remaining gap, and no apparatus can manufacture it.