Analyst & industry briefing
Governing what AI agents are allowed to do
For analysts, researchers and advisors covering enterprise AI governance. This page is the position, not a pitch — there is no trial to start from here.
- Agent
- Proposed action
- Resource
- Context
- Policy
- Allow / Warn / Approval required / Block
- Enforcement
- Evidence
- The category
- AI systems have moved from producing text to taking actions — running commands, changing files, calling tools, reaching services. Governing the text is a different problem from governing the action, and the controls that read a prompt do not sit where an action is executed.
- Execution-path governance
- Oconee evaluates a proposed action at the point it would be carried out, against the identity making it, the resource it touches and the context it arrives in — rather than inspecting the prompt that produced it.
- Deterministic authorization
- The decision is made by policy, not by a model. The same action in the same context produces the same verdict, which is what makes a decision reviewable after the fact and what separates this from asking one AI to supervise another.
- Enforcement evidence
- A decision is recorded with the identity, the context, the policy that produced it, the approval if one was required, and whether enforcement actually took effect — so the record answers what happened rather than what was intended.
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