Build a Personal AI Workflow Kit
Lesson 3: When Your Workflow Breaks – Diagnose, Fix, and Prevent
Lesson Objectives
By the end of this lesson, students should be able to:
- Diagnose the common failure modes of AI business workflows.
- Apply a targeted fix for each failure.
- Add prevention steps to their workflow kit.
Lesson Content
AI workflows fail in predictable ways:
- Missing inputs: someone runs the workflow without key facts. Fix: an input checklist that must be complete before running.
- Drift: outputs slowly change tone or length over weeks. Fix: a saved example of a good output to compare against.
- Invented details: the AI fills gaps with guesses (prices, dates, promises). Fix: "Use only the inputs; mark gaps as UNKNOWN."
- Tool changes: the AI tool updates and results change. Fix: rerun your test cases monthly.
- Wrong person running it: a new staff member skips review. Fix: put the review step in the SOP and train on it.
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