Decision Desk · Issue 09 · complete public learning edition

What Should Your AI Agent Be Allowed to Do?

Decide when an AI agent may send, spend, change records, move data, schedule work, or act through another system—and when it must remain propose-only.

Learning time90 minutes
Teaching12 cumulative lessons
InstrumentAuthority + reversal
DefaultDeny · propose first

Purpose → action → limit → approval → execution → reversal.

Agent autonomy is not one switch. It is a separate, enforceable decision for every action class, target, consequence, system, and environment.

01

Name the agent, purpose, and affected people

Gate
02

Inventory direct and downstream actions

Gate
03

Deny by default and enforce least privilege

Gate
04

Place informed approval before consequence

Gate
05

Observe execution and reconcile state

Gate
06

Stop, reverse, repair, and review

Gate

Twelve cumulative lessons.

Use supplied fictional workflows only. Never enter live credentials, personal records, security configurations, financial information, or executable instructions.

01
Issue 09

Separate recommendations from actions

Open

Generating, proposing, drafting, approving, executing, and confirming are different powers. Name the highest consequential step the agent can actually perform.

02
Issue 09

Define one actor and purpose

Open

Bind authority to one agent identity, version, owner, initiating user, environment, workflow, affected population, and purpose. A general-purpose agent has no general-purpose mandate.

03
Issue 09

Inventory every action class

Open

List messages, purchases, commitments, record changes, data movement, scheduling, deletion, access changes, external calls, and downstream triggers—including actions hidden inside tools.

04
Issue 09

Apply least privilege and deny by default

Open

Grant only the smallest roles, scopes, systems, records, fields, targets, amounts, volumes, and time windows necessary. Unlisted actions and destinations remain denied.

05
Issue 09

Place human approval before consequence

Open

Approval must show the proposed action, target, data, amount, uncertainty, source, and downstream effect before execution—not a vague confirmation after the action is queued.

06
Issue 09

Enforce limits outside the model

Open

Prompts are instructions, not access controls. Enforce spend, volume, target, rate, time, data, and action limits in permissions, policy layers, transaction controls, and receiving systems.

07
Issue 09

Control credentials and delegation

Open

Use agent-specific credentials, short lifetimes, narrow scopes, secure storage, rotation, revocation, and separation from the initiating person. Never let an agent acquire broader authority by asking another tool.

08
Issue 09

Design for partial failure and duplication

Open

Assume timeouts, retries, stale state, conflicting updates, repeated sends, partial transactions, and downstream success without confirmation. Use idempotency, state checks, and reconciliation.

09
Issue 09

Prove reversibility before autonomy

Open

Distinguish true undo from compensating action and irreversible consequences. Test rollback, fallback, restoration, notification, financial reconciliation, and affected-person repair.

10
Issue 09

Make action observable

Open

Log the initiator, model, tools, inputs, retrieved sources, proposed action, approval, execution, system response, state change, and errors without exposing secrets or unnecessary personal data.

11
Issue 09

Install stop and incident control

Open

Provide a reachable kill switch, credential revocation, queue pause, containment, evidence preservation, affected-party notice, incident ownership, and safe human continuation.

12
Issue 09

Issue an action-specific disposition

Open

Do not connect, keep propose-only, repair controls, or evaluate one bounded human-approved action. No authority transfers across actions, systems, users, environments, or versions.

Capability is not authority.

  • the agent, owner, initiating user, purpose, or affected population is unresolved
  • an action or downstream tool capability is absent from the authority inventory
  • a prompt or model refusal is the only limit on consequential action
  • approval happens after execution or hides the actual target, amount, data, or effect
  • the agent uses shared, persistent, overbroad, or nonrevocable credentials
  • duplicate, stale-state, partial-failure, or cross-system conflict behavior is untested
  • a material consequence cannot be reversed, compensated, reconciled, or clearly disclosed
  • logs, monitoring, kill switch, incident owner, or safe human fallback is missing

Agent Action Authority and Reversibility Matrix

Use fictional workflows only. Do not enter credentials, account details, security configurations, personal records, live instructions, or confidential information.

0/30action gates evaluated
An agent that can propose is not automatically allowed to act.
Each action class needs explicit authority, enforced limits, observable execution, tested reversal, and a human stop path.
Fictional action classPurpose allowedInputs authorizedApproval requiredLimit enforcedRollback provenAudit + stop works
Send an external message
Spend or commit funds
Create or change a system record
Move data between systems
Schedule, cancel, or trigger downstream work
Bounded disposition

Restoring your local matrix…

The educational product and reusable Authority and Reversibility Matrix are complete.

Real use still requires exact system and configuration evidence, security and legal review, enforced permissions, representative failure testing, verified approval and rollback, monitoring, incident rehearsal, affected-party safeguards, and organizational authorization.