1
Front Matter
5 chapters2
Part 1: Foundations — Understanding What You're Working With
7 chapters- Part 1: Foundations — Understanding What You're Working With
- Chapter 1: What AI Tools Actually Are (and Aren't)
- Chapter 2: How Language Models Think: A Conceptual Framework
- Chapter 3: The Right Mental Models for AI Collaboration
- Chapter 4: Trust Calibration — What AI Gets Right, What It Gets Wrong
- Chapter 5: Setting Up Your Personal AI Environment
- Chapter 6: The Iteration Mindset — Working in Loops, Not Lines
3
Part 2: The Art of Prompting
8 chapters- Part 2: The Art of Prompting
- Chapter 7: Prompting Fundamentals: Structure, Clarity, and Specificity
- Chapter 8: Context Is Everything: Loading Your AI's Working Memory
- Chapter 9: Instructional Prompting and Role Assignment
- Chapter 10: Advanced Prompting Techniques
- Chapter 11: Prompt Engineering Patterns for Recurring Tasks
- Chapter 12: Multimodal Prompting: Working with Images, Documents, and Data
- Chapter 13: Diagnosing and Fixing Bad Outputs
4
Part 3: Working with the Major AI Platforms
7 chapters- Part 3: Working with the Major AI Platforms
- Chapter 14: Mastering ChatGPT and GPT-4
- Chapter 15: Working with Claude: Strengths, Quirks, and Best Practices
- Chapter 16: Google Gemini and the Workspace Integration
- Chapter 17: GitHub Copilot and AI Code Assistants
- Chapter 18: Image Generation — Midjourney, DALL·E, and Stable Diffusion
- Chapter 19: Specialized and Domain-Specific AI Tools
5
Part 4: AI Across Professional Workflows
10 chapters- Part 4: AI Across Professional Workflows
- Chapter 20: Writing and Editing with AI
- Chapter 21: Research, Synthesis, and Information Gathering
- Chapter 22: Data Analysis and Visualization
- Chapter 23: Software Development and Debugging
- Chapter 24: Project Planning and Task Management
- Chapter 25: Decision Support, Analysis, and Strategic Thinking
- Chapter 26: Presentations, Slides, and Visual Communication
- Chapter 27: Business Communication: Email, Reports, and Documents
- Chapter 28: Customer-Facing Work: Sales, Support, and Outreach
6
Part 5: Critical Thinking, Verification, and Ethics
7 chapters- Part 5: Critical Thinking, Verification, and Ethics
- Chapter 29: Hallucinations, Errors, and How to Catch Them
- Chapter 30: Verifying AI Output — Fact-Checking Workflows
- Chapter 31: Understanding AI Bias and How It Surfaces
- Chapter 32: When NOT to Use AI (and Why That Matters)
- Chapter 33: Ethics of AI Use — Disclosure, Attribution, and Fairness
- Chapter 34: Legal and Intellectual Property Considerations
7
Part 6: Advanced Techniques and Automation
6 chapters- Part 6: Advanced Techniques and Automation
- Chapter 35: Chaining AI Interactions and Multi-Step Workflows
- Chapter 36: Programmatic AI — APIs, Python, and Automations
- Chapter 37: Custom GPTs, Assistants, and Configured AI Systems
- Chapter 38: Deploying AI in Teams and Organizations
- Chapter 39: Measuring Effectiveness: ROI, Quality, and Iteration Cycles
8
Part 7: Staying Current and Looking Forward
4 chapters9
Appendices
9 chapters- Appendix A: Prompt Templates Library (Quick-Reference)
- Appendix B: Python Code Reference for AI APIs
- Appendix C: Workflow Templates & Worksheets
- Appendix D: Tool Comparison Quick-Reference Cards
- Appendix E: FAQ — Common Questions and Frustrations
- Appendix F: Key Studies Summary (AI Cognition, Productivity Research)
- Appendix G: Glossary
- Appendix H: Answers to Selected Exercises
- Appendix I: Bibliography
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