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Redesigning Workflows Around AI Capabilities

7 chapters · 31 lessons

1. 1. Task Decomposition for AI Readiness

   4 lessons

   Break down your role into discrete tasks and classify them by input type, decision complexity, and handoff requirements.

2. 2. Matching Tasks to AI Capabilities

   5 lessons

   Learn which AI functions (drafting, classification, summarization, search, generation) fit specific work patterns and where they fail.

3. 3. Designing Human Review Checkpoints

   4 lessons

   Build review gates that catch errors, bias, and missing context before AI outputs affect decisions or customers.

4. 4. Building Feedback Loops That Improve Over Time

   5 lessons

   Create systems that capture what works, what fails, and how to refine prompts, data sources, and process design.

5. 5. Shifting Focus to Higher-Value Work

   4 lessons

   Identify which tasks become more important when routine work is automated, and adjust your role accordingly.

6. 6. Documenting Ownership and Accountability

   4 lessons

   Create clear records of who decides, who reviews, and who is accountable when AI is part of the workflow.

7. 7. Case Studies in Workflow Redesign

   5 lessons

   Walk through real examples of how project managers, analysts, developers, and operations teams redesigned workflows around AI.