First Principles in Scrum: Implementing Scrum and Agile Practices
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First Principles in Scrum: Implementing Scrum and Agile Practices

About the Book

Every week I get asked dozens of questions about Scrum from new Product Owners and Scrum Masters on every continent (except Antarctica). Most questions cannot be answered without going back to First Principles. This means you need to understand physics, biology, evolution, and psychology to do Scrum well.

I was the wingman of the sole surviving Ace from World War II in Vietnam. He was a brilliant scientist and engineer, and he taught me a lot about First Principles thinking. I was also lucky enough to engage with similar trailblazers in physics, chemistry, medicine, biology, and AI. They were all part of the search for hyperproductive Scrum, and they make for an exciting story.

In this book, I will share my insights on Scrum and First Principles thinking. I will also tell the stories of the trailblazers who helped me to develop my understanding of these concepts. I believe that this book can help you to become a more effective Agile Manager, Scrum Master or Product Owner.

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  • Categories

    • Computers and Programming
    • Scrum
    • Management
    • Agile Enterprise
    • Product Management
    • Scrum
    • Leadership
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About the Author

Jeff Sutherland
Jeff Sutherland, Ph.D.

Jeff Sutherland is the Inventor and Co-Creator of Scrum and Scrum@Scale and a Signatory of the Agile Manifesto.

Table of Contents

    • Note to Reader
    • Preface
    • The Agile Technology Stack: From Physics to Values to AI
      • The Agile Technology Stack: An Analogy
      • Start with First Principles
      • 1. Physics Layer (Agile’s “Physical Layer”)
      • 2. Biology Layer (Agile’s “Data Link Layer”)
      • 3. Neuroscience Layer (Agile’s “Network Layer”)
      • 4. Complex Adaptive Systems (CAS) Layer (Agile’s “Transport Layer”)
      • 5. Scrum Layer (Agile’s “Session Layer”)
      • 6. Scrum@Scale Layer (Agile’s “Presentation Layer”)
      • 7. Agile Values and Principles Layer (Agile’s “Application Layer”)
      • 8. AI Layer (Agile’s “eXtreme Agile Layer”)
      • Case Study: The Dysfunctional Scrum Team and the Agile Technology Stack
      • Case Study: The Downfall of Waterfall at AT&T and Bell South
      • Conclusion: Why You Should Never Use Waterfall
      • References
    • The Power of Bootstraps: From Computer Science to the Universe, Human Health, Scrum and AI
      • Introduction
      • The Magic of the Digital PDP7
      • Wolfram’s Physics Project: The Universe as a Bootstrap
      • Bootstrapping Cancer: A Computational Journey into Carcinogenesis
      • Ratfor: Bootstrapping a New Programming Paradigm
      • The iRobot Experience: Bootstrapping Intelligence from Simple Rules
      • Implications for Scrum and Beyond
      • Further Reading and References
    • How Scrum Emerged From First Principles
      • Introduction
      • The FBI’s Triumph and the Path to Empiricism
      • Taiichi Ohno’s Sage Advice and the Pursuit of Continuous Improvement
      • Scrum’s Origin in Lean and the Dance of Complex Adaptive Systems
      • Gödel’s Theorem and Computational Irreducibility: Unraveling Certainty
      • The Cathedral Unveiled
      • The FBI’s Triumph and the Path to Empiricism
      • Taiichi Ohno and the Pursuit of Continuous Improvement
      • Gödel’s Theorem and the Power of Empiricism in Scrum
      • Computational Irreducibility and the Emergence of Scrum
      • From Biology to Scrum: The Evolutionary Paradigm
      • The Transformative Power of Scrum: Shaping the Future of Product Development
      • References
    • The Paradox of Inductive vs Deductive Reasoning
      • Personal Prologue
      • Abstract
      • Introduction
      • The Paradox Explored
      • Conclusion
      • References
    • Responding to Change - Embracing the Paradox of Prediction and Adaptation
      • Introduction to the Paradox
      • Bayesian Surprise in Agile Environments: Friston’s Free Energy Principle
      • Free Energy in AI and Robotics
      • Free Energy in Agile Environments
      • Free Energy and Scrum Patterns
      • The Paradox of Prediction: A Dialogue Between Titans
      • Resolving the Paradox: The Agile Manifesto and Minimizing the Cost of Change
      • The Underappreciated Genius of the Agile Manifesto
      • Synthesizing the Paradox in Scrum Practice Across Industries
      • Conclusion: Scrum as Evolutionary Success
      • References
    • Understanding the Agile Mindset through the Wisdom of Four Warriors
      • Sun Tzu’s Art of Agile Leadership
      • Miyamoto Musashi’s Dual Swords: The Agile Leader’s Balance
      • Musashi’s “The Five Approaches” in Agile Context
      • The Musashi Meditation: A Daily Practice for Agile Leaders
      • Carl von Clausewitz and Agile Leadership: Navigating the Fog of War
      • John Boyd’s OODA Loop: The Agile Mindset’s Ultimate Weapon
      • Synthesizing the Warriors’ Teachings in Agile Leadership
      • Integration of Principles into a Comprehensive Agile Mindset
      • Integrating Warrior Wisdom into Scrum and Scrum@Scale
      • Conclusion
      • References
    • The Physics of High-Performing Teams - Unpacking Complex Adaptive Systems, the Seven Deadly Sins, and Seven Neural Accelerators in Scrum
      • Introduction
      • The Quantum Mechanics of Scrum: Unraveling the Physics of High-Performing Teams
      • Survival in a Complex World: The Imperative of Adaptation and Innovation
      • First Principles of Complex Adaptive Systems
      • Deviating from CAS Leads to the Seven Deadly Sins
      • Incorporating Neuroscience Accelerators into Scrum Principles
      • Conclusion: Embracing First Principles for High-Performing Teams
      • References
    • Scrum’s Secret Sauce: The Next Best Step
      • The Complexity and Importance of Prioritization in Scrum
      • The Next Best Step: A Cognitive Perspective, Quantum Mechanics, and the Power of Observation
      • Game Theory and Decision Making in Scrum
      • Driving System Evolution via Punctuated Equilibrium and Complex Adaptive Systems
      • The Role of AI: A ChatGPT Analogy and the Emergence of Expertise
      • Leveraging AI for Decision Making
      • The Human Element in Scrum Decision Making
      • Challenges and Potential Solutions
      • Real-World Applications and Case Studies
      • Future Implications: Welcoming AI onto the Scrum Team
      • Conclusion: The Next Best Step as the Key to Survival and Success**
      • References
    • The Secret Sauce of Scrum: Punctuated Equilibrium
      • Abstract
      • Introduction
      • The Secret Sauce of Scrum: Empirical Process Control and Punctuated Equilibrium
      • The Next Best Step: A Legacy from the First Scrum Team
      • The Role of AI in Identifying the Next Best Step
      • Conclusion
      • References
    • Early Finish, Accelerated Innovation: Harnessing the Buffer Pattern for Agile Story Completion in Product Development
      • Friston’s Free Energy Model of the Brain
      • Illigitimus Non Interruptus - Where It Comes From
      • Essence of the Buffer Pattern
      • References
    • Hierarchy and Autonomy in Scrum: The Influence of Holarchy and the Power of the People
      • Introduction
      • The Paradox
      • The Concept of Holarchy
      • Koestler’s Forethought: Complex Adaptive Systems in Scrum
      • Conclusion
    • Leveraging Scrum: Empowering Quality Excellence in Product Development
      • Introduction
      • The Evolutionary Approach of Scrum
      • Technical Debt and the Evolutionary Approach
      • The Impact of Computational Irreducibility on Scrum
      • Case Study: Systematic
      • The Scrum Framework and Quality
      • Emphasizing Early and Constant Testing
      • Shortening Delivery Time
      • Digital Management of Autonomous Teams
      • Impact of AI on Quality Assurance, Technical Debt, and Architecture
      • Continuous Customer Engagement
      • Humphrey’s Law and the Importance of Continuous Customer Engagement
      • Conclusion
      • References
    • Going From Average to Awesome: Why Teams That Finish Early Accelerate Faster!
      • Amazon’s Rigorous Approach: Teams on Probation and the Quest for Awesomeness
      • From Good to Great, Average to Awesome: The Quest for the Singular Data Point
      • Applying the Collins Method to Scrum Teams: A Surprising Discovery
      • Teams That Finish Early, Accelerate Faster: A Quantum Leap in Understanding Scrum
      • The Search for a Deeper Understanding
      • Friston’s Free Energy Model of Brain Function: The Key to Understanding Acceleration
      • Practical Implications for Scrum Masters
      • References
    • How to Make Agile Transformations Successful: Measuring Business Agility
      • Introduction
      • If the Failure Rate is 53% Why Do Companies Do Agile Transformations
      • Business Agility via Only Agile if it Generates Business Outcomes
      • Example of How Decision Speed Affects Business Agility
      • OODA Loop Decision Metrics
      • References
    • Aligning Agile Product management with the Laws of Physics, Simulation of Waterfall, Kanban, and Scrum
      • Introduction
      • The First Principle: Computational Irreducibility
      • Complex Adaptive Systems and Evolution
      • Product management Methods: Waterfall, Scrum, and Kanban:
      • Product management Simulation: Waterfall, Scrum, and Kanban
      • Parameters
      • Wolfram Code and Results
      • Scaling Agile: Addressing the Seven Deadly Sins
      • Scaling Agile: Addressing the Seven Generative Neuroscience Effects
      • Collaborative Environment and Social Neuroscience
      • Iterative Progress and the Zeigarnik Effect
      • Feedback Loops and Dopamine Reward System
      • Adaptive Change and Neuroplasticity
      • Empirical Process Control and Predictive Coding
      • Mirror Neuron Effect
      • The Vagus Nerve and Emotional Regulation:
      • Conclusion
      • References
    • Why Scrum@Scale: Taking Scrum to the Next Level
      • Background
      • Improvements Identified After Examining Millions of Scrum Projects
      • Conclusion
      • References
    • Why Scrum@Scale: Using a Hybrid Approach to Get Money for Nothing and Change for Free
      • Introduction: The Need for a Dual Operating System in Agile Transformations
      • Use Case 1: Balancing Current Operations with Future Innovation
      • Use Case 2: Overcoming Suboptimization with Constraint Theory and Scrum@Scale
      • Use Case 3: Ensuring Value Delivery with Systematic Measurement and Incremental Scaling
      • Use Case 4: Achieving Enterprise Agility with Scrum@Scale - Money for Nothing, Change for Free
      • References
    • Why Scrum@Scale: Digital Management of Autonomous Teams
      • Introduction
      • The Impact of the Emergence of Sentient AI
      • Technological Revolutions and Financial Capital (Perez)
      • Diffusion of Innovations (Rogers)
      • Crossing the Chasm (Moore)
      • Disruptive Innovation (Christensen)
      • Converging S-Curves and the Age of AI (Seba)
      • The Role of Digital Management in Agile Organizations
      • Speed of Innovation Began in Software Decades Ago
      • Tesla’s Digital Management of Autonomous Teams
      • Scrum@Scale Supports and Enhances Digital Management
      • References
    • Definition of Ready
      • Abstract
      • Introduction
      • Diverse Opinions on Definition of Ready
      • The Origin of Definition of Ready
      • Scrum and Complex Adaptive Systems theory (CAS)
      • The Systematic Case: Twice the Work in Half the Time
      • Balancing Readiness with Speed and Adaptability
      • The Role of Definition of Ready in Scrum
      • Benefits of Adopting Definition of Ready
      • Drawbacks of Adopting Definition of Ready
      • Finding the right balance
      • Conclusion
      • Future Directions
      • Final Thoughts
      • References
    • Epilogue: Our Journey Continues

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