Name the failure before it names the system.
A registry for source failure, agent error, overload, contradiction, economic pressure, and memory pollution — with fallback and recovery paths.
Every TheoB pathway can move through Past, Present, and Future without losing context.
Read current signals, conditions, and live context.
Voice ready
A resilient system does not pretend failure is rare.
TheoB should classify failure patterns before scale: source loss, agent error, overload, contradiction, economic pressure, and memory pollution. Each needs fallback and recovery.
A live feed, API, dataset, or source becomes unavailable, unreliable, or contradictory.
An AI agent hallucinates, misroutes, overreaches, or acts outside scope.
Too many signals, users, tasks, sources, or agent actions enter at once.
Sources, contributors, institutions, or agents disagree on a claim.
Sponsor, paid user, institution, or growth target pressures truth or governance.
Low-quality, private, contradictory, or outdated information becomes too persistent.