Persistent Agency
PAA treats the persistent agent — rather than an isolated model inference — as the relevant systems object.
The architecture examines how memory, identity, authority, state transitions and action remain governable across time.
Cognition and Commitment
PAA distinguishes exploratory cognition from state that becomes persistent, authoritative or consequential.
Free cognition. Controlled commitment.
Consequence and Recovery
Execution is not the end of the lifecycle.
PAA proposes that real-world consequence should return as new evidence, while recovery should construct or validate a trustworthy successor state when continuity is disrupted.
Persistent Agency Architecture
Modern AI systems are increasingly capable of maintaining memory, using tools, coordinating actions and operating across extended periods.
PAA asks a narrower systems question:
What architectural relationships are required when cognition becomes persistent, authority-bearing and capable of producing real-world consequence?
The framework draws from established and contemporary work in distributed systems, databases, security, provenance, trusted computing, runtime assurance, robotics and autonomous-agent research.
Its proposed contribution is not the invention of those constituent mechanisms, but a systems-level hypothesis about how they may need to interact in persistent autonomous systems.
A lifecycle view
Reality → Evidence → Observation → Interpretation → Belief → Candidate Decision → Commitment → Execution → Consequence → New Evidence
PAA examines where different classes of state may change freely, where stronger validation becomes appropriate, and where enforcement should become increasingly independent as consequence increases.
