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Who this is for

  • Knowledge workers who handle heavy document, reporting, and cross-department communication loads
  • Coordinators who want AI to take over repetitive workflow steps

Outcomes

  • Process long documents and multi-document sets with a six-step analysis method
  • Design clear, reusable context for AI tasks
  • Break a repetitive task into an executable, verifiable workflow

Competencies developed

  • AI Literacy
  • Prompt & Context Design
  • Verification & Evidence
  • Responsible AI & Data Safety
  • AI Application & Use-Case Design
  • AI Task Judgment
  • Instruction Design
  • Context & Source Awareness
  • Output Verification
  • Human-AI-Human Workflow
  • Responsible Use
  • Prompt vs. Context Diagnosis
  • Context Taxonomy
  • Context Quality Assessment (RAFS)
  • Context Strategy Selection
  • Context Failure Diagnosis
  • Context Canvas Design
  • Workflow Design
  • Agentic AI
  • Prompt, Workflow & Agent Diagnosis
  • Task Decomposition & Execution Steps
  • Workflow Pattern Selection
  • Decision Spectrum Classification
  • Basic Agent Loop
  • Verification Method Selection
  • Human-in-the-Loop Design
  • Agentic AI Workflow Canvas Design

Required before starting

None

  • AI 103 · Agentic AI Memory, Knowledge & Skills

Course sequence

  1. 1.AI 101 Claude AI Workforce Fundamentals
  2. 2.AI 102 Context Engineering: What Should AI Know?
  3. 3.AI 104 Agentic AI Workflow & Execution Design

Next step

AI 101 · Claude AI Workforce Fundamentals

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