Five rules that keep an AI agent accountable
An AI governance framework says who owns an AI agent, what the agent may touch, and when its owner reviews it.
Most frameworks run to dozens of pages. A revenue team needs five lines for each agent, written before the build:
- Owner. One named person accountable for what the agent does, never a committee.
- Boundary. What the agent may read, write, and send. Any action outside that list stays with a person.
- Log. Every action the agent takes is recorded and open to review.
- Review dates. Day 30, 60, and 90. Each review ends in a decision to rebuild, retire, or expand.
- Record. The Agent Job Description, the prompts, and the results sit in one place that your team owns.
Greenfield writes these five lines into the Agent Job Description before the build, so the review dates are on the calendar from day one. The boundary and the log follow the rules in your data stays yours.
The trace: agents reviewed on schedule are the leading indicator. The metric each agent was hired against follows. Predictability is where it lands.
The example is the agent from a pipeline that reports on itself. We build and review agents like it in Agentic Workflows.
Who owns the last agent your team switched on?