Organic Prompting
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Organic Prompting

Solving real problems with natural language prompts

About the Book

Solving real problems with natural language prompts

About the Author

Adam Russell
Adam Russell

Adam writes about project management on his blog “Adam On Projects” and in his books and other content at He is also an expert in applying ChatGPT to project environments and has written several books on ChatGPT.

Adam coaches and mentors other project managers, and consults on various projects around the world.

Adam Russell has successfully delivered software development, software package, and systems integration projects for nearly 40 years, using both Agile and traditional approaches.

Adam started as a software developer, and then moved into pre-sales technical support when the IBM PC launched. He launched his project management career after he helped to close a significant government deal. The head of projects said: “You helped sell it. Now, you can deliver it”.

Since then, Adam has worked for companies ranging from 1-person startups to global tier-1 vendors and customer organisations in roles ranging from hands-on project manager through to General Manager of Systems Integration.

In those roles, Adam has been responsible for delivering hundreds of projects, ranging in budget from $5k up to over $100m. Adam also volunteers his time and skills with non-profit organisations.

Table of Contents

    • Getting Engaged with this Book and its Author
    • Notes about this version
    • Introduction
    • How to Read This Book
      • Outline of this Book
    • Start Here
      • Start with simplicity
      • First, Action!
      • Second, Critically Evaluate!
    • Organic Prompting Overview
      • Organic prompting
        • Organic Prompting Design Parameters
        • Benefits of Organic Prompting
        • Organic Prompting - A Compelling Alternative
        • The Foundations of Organic Prompting
        • Principles of Organic Prompting
        • Example of Organic Prompting
        • Organic Prompt “Nudges”
      • Prompt Engineering vs. Organic Prompting: A Comparative Analysis
        • Why Not Just Start with Prompt Engineering?
        • The Pros and Cons of Prompt Engineering
        • The Unique Benefits of Organic Prompting
        • When is Organic Prompting The Wrong Approach?
        • Conclusion
      • Misunderstanding ChatGPT Weaknesses as Strengths
        • Don’t Mistake the Result with the Function
        • Don’t Mistake the Result with Skills
        • Don’t Mistake the Result with Intelligence
        • The Bottom Line
    • Initial Self-assessment
      • Crossing the Skills Bootstrapping Chasm
        • What’s your problem-solving “Mindset”?
        • How much do you know about the problem domain?
        • What role do you expect ChatGPT to play in your solution?
        • Conclusion
        • What’s your solution strategy?
      • Diagnostic Tools
        • Paradigm Zero Mindset
        • Enablement Objective (Automation vs Augmentation)
        • Domain Expertise vs Content Contribution Mix
        • User and AI Domain Expertise
    • Organic Prompting Framework
      • Organic Prompt Design Guidelines
        • Prompt Design Goals
        • Satisficing is Satisfaction
        • Conclusion
      • The Foundations of Organic Prompting: A Natural Language Approach
        • The Rise of Prompt Engineering
        • Is Prompt Engineering the Only Way?
        • What is “semantic contamination” and how do I avoid it?
        • Impact of Semantic Contamination on Prompting
        • Strategies to Mitigate Semantic Contamination
        • Avoid Semantic Contamination with Organic Prompting
        • Expanding on Techniques
      • Evolutionary Prompt Development
        • Generic Evolutionary Cycle
        • Applying the Generic Evolutionary Cycle to Prompt Development
      • Three Cycles of Interaction with ChatGPT
        • 1. Initial Inputs
        • Cycle I: Prompt Development and Refinement
        • Cycle II: Producing Desired Results
        • Cycle III: Seeking External Information
        • Fitness Function
        • Conclusion
      • Evolutionary Development and Improvement of Prompt Efficacy
        • Knowledge / Mastery of the Problem Domain
        • Skill and Experience with Prompt Structure and Efficacy
        • Scope and Capabilities of the End-to-End Solution Construct
        • Natural Language Binding
        • Riding the Evolutionary Cycle - Keep Working the Edge!
        • Conclusion
      • Interaction Use Cases
        • Overview of Interaction Components
        • Basic ChatGPT Interaction Data Patterns
      • Organic Planning
        • Basic Interacting with ChatGPT
        • From Interaction to I-P-O
      • Bridging Organic Prompting to Prompt Engineering: A Guide for Beginners
        • Introduction
        • Understanding the Basics of Prompt Engineering
        • Core Concepts of Prompt Engineering
        • Getting Started with Prompt Engineering
        • Step-by-Step Guide
        • Conclusion
      • Bridging Organic Prompting into Prompt Engineering: Understanding Prompt “X-Shot” Patterns
        • Introduction
        • Zero-Shot Prompts
        • Benefits of Zero-Shot Prompts
        • One-Shot Prompts
        • Few-Shot Prompts
        • Multi-Shot Prompts
        • Why Use “X-Shot” Patterns?
        • Conclusion
    • Deep Self-assessment
      • Self-Assessment - Your Perspective on the World
      • Self-Assessment - Domain Knowledge/Experience
        • Scale of Domain Mastery
        • Domain Mastery Characteristics
    • Detailed Solution Assessment
      • Solution-Assessment: Your Approach to Problem Solving
        • Automation vs Augmentation: Choosing the Right AI Strategy
        • Automation/Augmentation Scale Characteristics
      • Solution-Assessment - Content Contribution in the Solution
        • Scale of Contribution Mix of AI-Assisted Content Creation
        • Characteristics of the Scale
      • Solution-Assessment - Intended Distribution Workflow
        • Scale of Workflow Distribution
    • Detailed ChatGPT Capability Assessment
      • ChatGPT and Its Capabilities: Analysing Test Performance
        • Introduction
        • Tests Passed by ChatGPT
        • Details of the Tests
        • Inferences from ChatGPT’s Test Performance
        • Conclusion
    • Analysing the Assessments
      • The Impact of Personal Mindset on ChatGPT Use
        • Paradigm Zero and Organic Prompting:
        • Impact on Prompt Development and ChatGPT Interaction
        • Heuristics for Optimising ChatGPT Use
        • Conclusion
      • Domain Expertise vs Content Contribution Mix
      • User and AI Domain Expertise
      • Enablement Objective (Automation vs Augmentation)
      • Response Variability
      • Domain Change & Complexity
      • Accuracy vs Relevance
      • Execution Cycle
    • Wrap & Where to From Here?
    • More from Adam Russell
    • Copyright

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