Proof-Carrying Agent Actions: Model-Agnostic Runtime Governance for Heterogeneous Agent Systems
arXiv:2606.04104v1 Announce Type: cross Abstract: Agent systems execute through runtimes with very different control points: local coding tools, framework SDKs, managed agent platforms, API gateways, and observer-only integrations. A high-risk action such as publishing data externally may therefore appear as a shell command in one runtime, a tool call in another, and a hosted session transition in a third. This makes it difficult to answer a basic governance question consistently: what action was authorized, under whose authority, with what approval semantics, and with what evidence after exec
The proliferation of AI agents across diverse and fragmented execution environments necessitates robust runtime governance solutions as these systems move towards deployment in sensitive applications.
Organizations and governments deploying AI agents require clear accountability and auditability for agent actions, especially concerning critical functions, to prevent misuse and ensure compliance.
The ability to consistently track, authorize, and verify agent actions across heterogeneous platforms becomes possible, enabling safer and more auditable AI agent deployments.
- · AI agent platform providers
- · Compliance and risk management software vendors
- · Enterprises deploying AI agents
- · Shadow IT departments
- · Organizations with opaque AI systems
Increased trust and adoption of AI agent systems in regulated and high-stakes environments.
Development of new regulatory frameworks and standards specifically targeting AI agent governance and accountability.
The integration of proof-carrying actions into smart contracts, enabling decentralized and auditable AI agent interactions.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.AI