Degradation and Recovery

A truth machine may lose adaptive capacity without losing or corrupting its accepted account.

Durable minimum

TM-DEC-001 — Last accepted truth. Failure of an AI Peer, model provider, reconciliation worker, user interface, live observer, or publication surface MUST NOT alter or erase the last accepted current truth.

TM-DEC-002 — Completed decisions survive. Accepted changes, their evidence references, reviewers, rationale, and resulting states MUST remain recoverable without relying on the session or process that produced them.

TM-DEC-003 — Partial work is not current. Interrupted admission, reconciliation, validation, application, or publication MUST NOT expose a partly advanced coherent state as current.

TM-DEC-004 — Recoverable uncertainty. Queued evidence, proposed changes, failed work, and unknown observations SHOULD remain distinguishable and recoverable after interruption.

TM-DEC-005 — Declared degraded behavior. An implementation MUST state which reads, deterministic operations, intake paths, and publication paths remain available when each material adaptive or external dependency fails.

AI independence

TM-DEC-006 — No model safety dependency. Core correctness and recovery MUST NOT require a particular model, model memory, or conversation history. If the system uses an AI Peer, the durable workspace must be sufficient for a capable replacement to inspect the accepted account and its operating rules.

Recovery evidence

Backups are not self-proving. A consequential implementation should retain dated evidence that accepted truth, evidence integrity, change ancestry, and current selection can be restored together. Deployment rollback and truth rollback are different operations: restoring application code must not silently reverse accepted domain truth.