Optional · Professional Practice · Lesson 06 of 08
How to Build an AI Workflow
One successful result proves that something worked once. A workflow has to survive the next file, an interrupted connection and a result that needs human judgment. Its design is as much about those ordinary failures as the ideal demonstration.
Related foundation: How to Verify AI Output →
Where should the boundaries of automation sit?
A process map from source to final action makes consequential steps visible. Messages, orders, publication, payments and destructive changes need the appropriate human approval before execution. Inputs, versions, outputs, exceptions and disposition should remain traceable. A generated draft reaching the end of a sequence does not itself authorize the external action.
What should the prototype establish?
A manual trial exposes the decisions the automation must preserve. Normal operation, failure, retry, rollback and escalation all need an owner and a tested path. Completion quality, correction effort and time saved reveal whether the process improves the work. Frequent execution alone is not evidence of usefulness if the team repeatedly repairs the result afterward.
How should a failed workflow recover?
Automated external actions need to stop while the last correct input, approval and system state are established from preserved records. A safe manual route allows necessary work to continue. The cause may lie in data, prompts, integration, permissions or destination behavior. A restart needs the failure tested, rollback practical and retries unable to duplicate actions. Monitoring should confirm the accepted result, not merely that the sequence ran.
Sources and further reading
Try a defined task
AI workflow sketch
Connect the steps without losing human judgment.
Reviewed September 2026 · Inspire Hardware