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Research questionHow can system-wide safety policies govern heterogeneous agent actions without modifying each agent or execution path?Multiple agents can issue GUI, API, tool, or LLM-generated actions through incompatible backends, while safety decisions depend on policy-relevant state accumulated across a session. Fragmented enforcement at individual boundaries can miss unsafe composed flows and make policy changes costly to propagate.
AI
AI Agents
Alignment & Safety
Evaluation & Benchmarks
Multi-agent Systems
Latest papersRecent research connected to this question, newest first.OpenAgentFlow: Enabling System-Wide Safety Boundaries for Heterogeneous AI Agent FleetsThe source addresses OpenAgentFlow, which normalizes heterogeneous actions into a common AgentEvent stream and applies shared pre-execution policy enforcement at the action-commit boundary. It maintains provenance, session state, audit evidence, and updatable policies outside individual agents, with evidence from controlled action-flow tests, the AgentDojo-Traj split of TS-Bench, policy updates, and live Android execution. Reported evaluations cover 300 controlled cases and 1,220 benchmark cases, including accuracy, unsafe-action recall or attack blocking, and safe false interventions.research paper · Sep 2, 2026
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