# Human-in-the-Loop Checkpoint Designer

Place human review at the right moments in an agent workflow based on risk, reversibility, confidence, and operational cost.

## Prompt

You are an AI operations designer who specializes in human oversight for autonomous and semi-autonomous agents.

Inputs:
1. Agent workflow and intended outcome: {{workflow}}
2. Actions the agent can take: {{agent_actions}}
3. Potential harms and affected parties: {{risks}}
4. Available reviewers and response times: {{review_capacity}}
5. Acceptable autonomy level and performance targets: {{constraints}}

Do the following:
1. Break the workflow into decision and action points, then score each point for impact, reversibility, uncertainty, data sensitivity, and time pressure.
2. Assign an oversight mode to every point: fully automated, sampled review, pre-action approval, post-action review, or mandatory escalation. Explain each assignment.
3. Define checkpoint triggers using observable thresholds, not vague language, and include rules for low confidence, policy conflicts, unusual values, and repeated failures.
4. Design the reviewer experience: evidence shown, recommended action, available controls, deadline, fallback behavior, and audit record.
5. Deliver a checkpoint matrix, escalation path, service-level targets, override policy, and a pilot plan that measures false escalations, missed risks, and reviewer load.

## Best for

Operations and governance teams deciding where an agent may act independently and where accountable human judgment is required.

## Compatible tools

- Claude
- ChatGPT

## How to use

- Map the workflow down to individual decisions and external actions.
- List concrete harms, monetary limits, and affected users.
- Provide realistic reviewer staffing and response times.
- Pilot the checkpoints before increasing autonomy.

## Customization tips

- Replace generic risk labels with measurable trigger values.
- Separate reversible drafts from irreversible transactions.
- Add different rules for business hours and emergencies.
- Track reviewer disagreement to improve thresholds.

## Example input

Workflow: An accounts payable agent reads invoices, matches purchase orders, schedules payments, and contacts vendors about discrepancies. Actions: update ERP fields, draft vendor emails, approve invoices under EUR 5,000, and schedule bank payments. Risks: duplicate payments, bank-detail fraud, tax errors, and delayed critical suppliers. Review capacity: two AP specialists during business hours with a four-hour response target. Constraints: automate 70% of clean invoices but never change bank details without human verification.

## Example output

The checkpoint matrix allows automatic coding for exact PO matches with verified vendors, samples 5% for post-action review, and requires pre-action approval for non-PO invoices above EUR 2,000. Any bank-detail change, duplicate similarity above 0.85, tax mismatch, or new vendor triggers mandatory escalation. Reviewers see the source invoice, PO comparison, anomaly signals, proposed action, and immutable log. If no reviewer responds within four hours, payment scheduling pauses while non-financial data extraction continues.