What Belongs in an AI Agent Workflow Before Launch
A practical launch framework for agent boundaries, review loops, data access, escalation rules, and measurement.
Start with boundaries.
An AI agent workflow needs a clear job before it needs more tools. Define what the agent can do, what it cannot do, and which decisions require human review.
Without boundaries, the workflow becomes difficult to trust.
Give the agent the right context.
Useful agent workflows depend on clean inputs and constrained access.
- Source documents and systems.
- Customer or account context.
- Approval requirements.
- Escalation paths.
- Output format expectations.
Add review loops before launch.
The first version should produce work that can be inspected. Human review gives the team a way to catch errors, improve prompts, and define the cases where automation is reliable enough to expand.
- Log agent inputs and outputs.
- Review a sample of completed runs.
- Track correction reasons.
- Update instructions based on recurring misses.
Measure business impact.
Do not measure the workflow only by tokens or task count. Measure time saved, error reduction, speed to response, conversion lift, or operational throughput.
