Autonomous execution
The agent may perform the action within defined conditions without case-by-case approval.
Authority & Human Checkpoint Design
Decide what the agent may do — and where a person must take over.
Agent autonomy is not a binary choice. Different actions in the same workflow carry very different consequences — and the authority model should say so explicitly.
Autonomous executionwithin defined conditions, no case-by-case approval
Execute with checkpointprogress to a defined point, then obtain review
Propose onlythe agent prepares, a person decides
Human onlyoutside agent authority entirely
Overview
An agent may safely execute some tasks, propose others, and be prohibited from deciding some at all.
Authority & Human Checkpoint Design defines those boundaries explicitly and connects them to the effective process, risk context, and organizational accountability.
Objective
Create an authority model that enables useful autonomy without silently delegating decisions that should remain human.
Authority modes
Four modes, assigned per action.
Execute with checkpoint
The agent may progress until a defined point and must obtain human review or approval before continuing.
Propose only
The agent prepares an analysis, recommendation, or change, but a person decides whether it is accepted or executed.
Human only
The decision or action remains outside agent authority.
Design inputs
Authority can depend on
- Task type
- Risk
- Product context
- Safety classification
- Regulatory constraints
- Financial or organizational impact
- Tool permissions
- Confidence
- Evidence availability
- Independence requirements
How the service works
Five steps from decision points to enforced governance.
Identify decisions and actions
Decompose the workflow into meaningful execution and decision points.
Assess consequence and accountability
Understand what can happen if the action is incorrect or uncontrolled.
Assign authority mode
Determine the appropriate level of autonomy for each point.
Design checkpoints
Specify who reviews, what evidence is presented, what decision is required, and what happens on rejection or uncertainty.
Implement governance
Connect authority rules to agent instructions, access controls, hooks, workflow states, and provenance.
Every checkpoint specifies
- Who reviews
- What evidence is presented
- What decision is required
- What happens on rejection
- What happens on uncertainty
Deliverables
- Authority matrix
- Action and decision classification
- Mandatory human checkpoints
- Escalation model
- Approval evidence requirements
- Implementation specifications
Benefits
- Make the limits of agent autonomy explicit rather than emergent.
- Keep accountable decisions with accountable people.
- Give reviewers the evidence a decision actually needs.
- Let autonomy widen safely as confidence grows.
Enforced by
Deterministic Control Implementation
How the boundaries get enforced rather than merely stated.