Counterfactual Tests Expose Joint Dependence
Removing one channel, agent, or incentive can show whether a suspicious outcome depends on coordination.
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Agent Evaluations Need Incentives, Not Just Tasks
Agents that cooperate in neutral benchmarks may coordinate differently when rewards create shared private advantage.
A Collusion Benchmark Needs Ground Truth
Without controlled channels and incentives, benchmarks cannot tell true coordination from coincidental correlation.
Collusion Monitoring Must Preserve Privacy
Cross-agent visibility can improve security while creating a dangerous central record of prompts, identities, and business activity.
A Guardian Agent Must Be Independent Enough to Disagree
A monitor that shares the same incentives, model, data, and operator may reproduce the failure it is meant to catch.
Guardian Agents Need Separation of Duties
One guardian should not observe, judge, approve, execute, and erase the evidence for the same event.
When Should a Guardian Agent Intervene?
Too little intervention permits harm; too much turns normal cooperation into friction and false accusation.
Agent Governance Should Link Every Rule to Evidence
Policies become credible when reviewers can see which events, relationships, and assumptions triggered them.
Incident Response Must Follow the Agent Graph
Compromising one agent can affect delegated tasks, shared memory, tools, counterparties, and decisions already in progress.
Apply the AI RMF to Agent Relationships
Managing each model independently misses risk that appears only when agents delegate, compete, and transact.