
CEO, CIO, CTO
Data platforms and applied artificial intelligence from a business perspective.
| Part | Topic |
|---|---|
| Prologue | |
| Part 1: "Framing Technology Investment" | |
| Why Does a Company Need to Grow? | |
| The Challenges of Growth | |
| Structural Transformation | |
| What is Knowledge Work? | |
| The Rise of the Information Economy | |
| The Red Queen's Game | |
| How Technology Investment Enables Growth | |
| Part 2: "Building Knowledge Work Platforms" | |
| Knowledge Work Architecture | |
| Analyzing Knowledge Work Architecture | |
| Data Integration | |
| What is a Data Platform? | |
| It's All Games of Materialized Views | |
| The Information Layer | |
| What is Data Engineering? | |
| Transform Engineering | |
| How Data Platforms Change as Companies Grow | |
| Modernizing Data Platforms | |
| The Cost of Coordination | |
| The 3 Ways A Business Uses Technology | |
| Part 3: "The Evolution of Knowledge Work" | |
| The Evolution of Knowledge Work | |
| AI is Just Productivity You Don't Understand Yet | |
| All You Need is More Productivity | |
| What is Artificial Intelligence? | |
| There's No Such Thing as Artificial Intelligence | |
| Why is it so hard to sell Artificial Intelligence Tools? | |
| What is Generative AI? | |
| Decision Intelligence | |
| Conversational User Interfaces | |
| Built for the Wrong Audience | |
| Part 4: "The Tao of Work" | |
| Physical Labor and Cognitive Labor | |
| Defining Tools | |
| Defining Personhood | |
| Can Tools Exist Without Humans? | |
| The Value of Human Capital | |
| Reading is Fundamental | |
| Epistemic Madness | |
| What Constitutes 'Responsibility' for Work? | |
| How Writing Allowed Information to Become Infrastructure | |
| What is Agency? | |
| The Agency Trap | |
| How Agency Bounds Automation | |
| The Fallacy of Autonomy | |
| Part 5: "The Limits of Knowledge Work Tools" | |
| What is Reasoning? | |
| What About AGI? | |
| The Connection Between Reading, Writing, and Reasoning | |
| Do Large Language Models Reason? | |
| Polanyi's Paradox | |
| Tacit Understanding | |
| The Deterministic Nature of Traditional Computation | |
| Automated Reasoning is Subjective Computation | |
| How Automated Reasoning is Different from Traditional Computation | |
| Epistemological Drift | |
| The Durability of Determinism | |
| Part 6: "The Mechanization of Cognitive Labor" | |
| The Mechanical Loom of Mental Synthesis | |
| Cognitive Labor: The Mental Work Behind Knowledge Work | |
| The Types of Task Automation | |
| The Verification Gap | |
| The Cognitive Backplane of Oversight | |
| The Challenges of Risk with Automation | |
| Deconstructing the Underwriter Under Automation | |
| The Minimum Viable Person | |
| A Map for LLM Automation | |
| Part 7: "The Economics of Cognitive Labor" | |
| What Happened to Physical Labor Roles After Mechanization? | |
| Jevon's Paradox | |
| Early Cognitive Labor Evolution After Tools: 1950–2000 | |
| Rebounds and O-Rings | |
| The Evolution of the Underwriter | |
| The Layers of Knowledge Work | |
| A Value model for the Structural Transformation of Knowledge Work | |
| Part 8: "The Future of Work" | |
| Will Agents Replace People? | |
| Where Are All the Jobs Going? | |
| The Automation Treadmill | |
| How Work Evolves Under Automation | |
| The Automation Closure | |
| You Can't Go Home Again | |
| Appendix Chapters: "Knowledge Work in Industry" | |
| How Smart City Investment Enables Regional Economic Growth |
The rise of Large language models, such as openAI, are advanced artificial intelligence systems designed to understand and generate human-like text. They have also kicked off a new cycle of artificial intelligence hype, research, and investment. However, organizations still struggle with the foundations of building and operating data platforms to run their core business.
The Hitchhiker’s Guide to Knowledge Work introduces the challenges and complexities of modern knowledge work, particularly in industries reliant on expertise and information processing. It emphasizes how traditional management approaches often fail to address the unique demands of knowledge workers, who require autonomy, adaptability, and effective collaboration to succeed.
This online book will allow you to better understand not only "what is knowledge work?", but also how knowledge work is co-evolving with technology and changing the economic labor distribution. This book will set you up to better frame how you should form your technology inventment thesis into both data platforms and articificial intelligence in a way that focuses on making your business more productive and cutting through the hype.
Get PDF
Feedback / Contact Us
If you'd like to share a comment about our work (typos, other papers, etc) or want to talk about potential use cases, feel free to reach out to us.