Implementation planning

AI Agent Implementation Checklist

An AI agent implementation checklist helps you move from a promising workflow to a controlled first version.

Implementation steps

1. Define the workflow

Trigger
Expected output
Workflow owner
Systems involved
Review point
Success measure

2. Prepare the data

Source documents or records
Allowed data fields
Restricted data fields
Rules for missing or stale data
Sensitive data boundaries

3. Set tool permissions

Read-only tools
Update tools
Tools that need approval
Tools the agent must not use
Error handling for failed calls

4. Write the instructions

The instructions should name the goal, allowed actions, review point, output format and refusal behavior. They should also explain what to do when information is missing.

5. Test with realistic cases

Test normal cases, edge cases, missing data, wrong data, duplicate requests and rejected outputs. The first version should be small enough for a person to inspect.

6. Launch with logs and ownership

Before release, confirm who reviews the output, where logs are stored, how errors are handled and when the workflow should be paused.

Start with readiness if the workflow is not mapped

The implementation checklist works best after the workflow passes the readiness check.

Request the checklist Review readiness first