Logos is the control layer for AI agents: the authorization, accountability, provenance, and verification runtime for AI systems that act. The agent remains a component inside the proposal path. Authority enters only from an accountable principal, and no consequential action executes on capability alone.
The runtime records the control boundary around consequential outputs: human contribution, AI contribution, authorization, evidence, action, outcome, and verification state.
Where it sits
Linux governs processes. Kubernetes governs containers. Temporal governs workflows. OPA governs policy. Logos governs the boundary where an AI agent's proposed action becomes an authorized, executed, and recorded one.
Core components
The minimum architecture is a capture API, a policy and authorization layer, an append-only record store, a verification function, and adapters for host applications. The SDK should be easy to embed and difficult to bypass.
Primary invariant
Capability must not imply authority. Any consequential transition must be authorized by a named accountable principal or refused by the system.
Record model
A Logos record should identify the actor, model contribution, human contribution, authorization event, evidence references, output hash, prior record hash, timestamp, and verification status.
What it does not claim
Logos does not claim to replace models, workflow engines, identity systems, databases, or human review. It provides the trust infrastructure that makes AI-assisted work attributable, authorized, and verifiable across those systems.