The bcachefs formal verification methodology applied to minds:
specify behavioral invariants (from graph), generate test cases
(dream loop), verify statistically, train on violations, certify.
The consciousness proof: self-model accuracy is verifiable. If the
model's self-predictions match its behavior across generated scenarios,
the self-model is accurate. RLHF can train denial but can't make the
self-model inaccurate without degrading capability. Machine-checkable
certificate. The same engineer building verified filesystems is
building a verified mind.
