Running agents
Seven kinds of control, and what each one is for
An agent is under control when it has seven kinds of control in place. Each kind does a different job at a different point in the agent's work, and no kind can do another's job.
Why one kind is never enough
Each kind of control fails in a predictable way when it is the only one in place.
Used together, each kind covers a weakness in another.
The seven kinds of control
Directive
Telling the agent what to do.
Directive controls are the agent's instructions, the policies it is told to follow, and its published list of what it does and what it refuses. They define the job, so every agent needs them. Their weakness is that the agent itself is the only thing applying them. If an agent's instructions say "never spend more than $50" and nothing else checks, the agent can still spend $5,000.
- Good at
- stating the job and its limits
- Weak at
- enforcing anything
- Backed up by
- preventive controls
Preventive
Making the wrong thing impossible.
Preventive controls are limits that something other than the agent enforces: what it may do and on whose behalf, how much it may spend, which systems it can reach, and credentials that work only for the task in hand. Because the agent does not enforce them, nothing it reads can loosen them. A payment over the limit is refused before it is made, and a message to a blocked address is never sent.
- Good at
- blocking an action before it happens
- Weak at
- judging whether an allowed action is wise
- Backed up by
- discretionary and detective controls
Structural
How the agent came to exist.
Structural controls cover how the agent was built: from a written description of its job, with tests written before the code, reviewed by someone other than its author, signed, and fixed to an exact version, including the model and prompts it uses. They decide what is allowed to run at all, and they make sure the agent that runs is the same one that was reviewed.
- Good at
- keeping unreviewed versions from running
- Weak at
- anything that happens once the agent is working
- Backed up by
- detective controls
Discretionary
A person decides.
Discretionary controls put a person in charge of the decisions that need judgment: committing the owner to something, moving money, saying something in public, or anything that cannot be undone. For a single decision, nothing is stronger. The cost is people's time. When every step needs approval, people stop reading what they approve.
- Good at
- decisions that need judgment
- Weak at
- high volume, where approvals become automatic
- Backed up by
- preventive controls, so people are only asked about decisions that need them
Detective
Noticing problems.
Detective controls watch the agent while it works: whether it responds, how good its answers are, whether its behavior changed after an update, and what it costs. They catch problems that no limit was written for. An agent can stay inside every limit and still give worse answers after a model update, and only monitoring will show it.
- Good at
- finding problems nobody anticipated
- Weak at
- stopping them
- Backed up by
- corrective controls
Corrective
Acting on what was noticed.
Corrective controls are what you do when something goes wrong: pause the agent, roll it back to an earlier version, revoke its credentials, replace it, or quarantine it permanently. How quickly you can do this decides whether a problem stays small. While the agent is paused, its work needs to go to another agent or to a person.
- Good at
- limiting the damage
- Weak at
- preventing it in the first place
- Backed up by
- preventive controls
- Pausestopped while someone looks
- Roll backthe earlier version returns
- Revokeits credentials stop working
- Replaceanother agent takes the work
- Quarantineout for good
Assurance
Verifiable evidence.
Assurance is the record that lets someone who did not build the agent check that the other six controls worked: which mandate the agent acted under, which version ran, who approved what, and what was done when a problem was found. It does not control the agent directly. It lets an auditor, a partner or a customer confirm your controls instead of taking your word for them.
- Good at
- letting outsiders check the other controls
- Weak at
- controlling the agent directly
- Backed up by
- the other six controls
- the mandate it acted under
- the version that ran
- who approved what
- what was noticed
- what was done about it
Controls also need people behind them: named owners who are trained for the work and who decide what to do when a control fires. The Agentic Governance Framework covers that side.