Preface: A Career Through Acceleration

Summary

The preface grounds the entire book in lived experience of technological acceleration. Rather than abstract theorising, the author traces four decades of professional involvement in technological disruption: from building early computers in the Caribbean through the rise of the internet, Web 2.0, smartphones, and now artificial intelligence. Each shift arrived faster than the previous one, and each shift transformed what "expertise" meant.

The central insight isn't that the future is changing—it's that the acceleration itself is the story. The time between technological breakthrough and widespread deployment continuously shrinks, making institutions built for gradual change obsolete mid-lifecycle.

Key Arguments

Acceleration compounds: Each technological era arrived faster than the previous one. From computers (decades to mainstream) through internet (years) through smartphones (months) to AI (immediate integration)
Expertise becomes commodified overnight: Twenty-five years of accumulated judgment about benefits administration became data points in an AI model that displaced all of it in milliseconds. Knowledge capital that took decades to build evaporates when machines learn it in hours
Institutional lag is real and worsening: Every organisation the author observed struggled to adapt faster than capability changed. The gap between what was possible and what was permitted widened with each cycle
The vocabulary for this doesn't exist yet: The transition creates categories that society lacks names for. Not unemployed (receives income), not retired (too young), not working (the job no longer exists). Language itself fails
Consciousness must shift before structures can shift: The author defines themselves entirely through what they build, teach, and create—yet argues the book itself is about learning to think beyond this framework

Key Concepts Developed

Technological velocity over vision: Specific predictions about the future consistently miss direction, but the pattern of "arriving faster than expected" proves reliable
The expertise trap: Expertise becomes a liability when the domain itself transforms. The expert's advantage disappears when machines consume the entire knowledge domain instantly
Institutional design for stability fails under acceleration: Organisations built for gradual adaptation face obsolescence when change compounds exponentially
Identity dissolution at scale: When your identity is defined by what you do professionally, and the profession disappears, the person fragments

Evidence Used

Personal career trajectory across sectors: from hardware to software to the internet to AI
Specific technological migrations: fax to email, static websites to dynamic, Flash to mobile, traditional AI to generative AI
Institutional responses: 60-page business plans becoming 10-page, then instant investment decisions
The knowledge economy paradox: more information to process means shorter window to communicate it

Historical Pattern

The preface doesn't argue for a specific technological future but establishes that previous predictions about AI, timelines, and disruption have consistently underestimated the actual pace of change. The author has lived through decades where conservative estimates proved too conservative.

The Uncomfortable Self-Reflection

Unlike many tech proponents, the author ends by acknowledging the irony: they argue society must change consciousness to adapt whilst remaining entirely trapped in the old consciousness themselves. The book is written by someone demonstrating the very problem they diagnose—expertise as identity, productivity as worth. This honesty establishes the scope of consciousness shift the book claims is necessary.

Editorial Notes

The preface establishes essential credibility: the author has observed technological change professionally for four decades, built inside the transformations, and watched institutions repeatedly fail to adapt. This positions subsequent arguments as grounded observation rather than speculation. The willingness to acknowledge personal limitation (own identity trapped in outdated model) prevents the book from claiming false certainty. The preface also introduces Chantal as the reader's guide through concrete human experience of these changes.

Manuscript Content

The text below mirrors the current source-of-truth manuscript at chapters/00-preface.md (synced from the Google Doc on 2026-04-20). Treat this section as read-only reference; edit the chapter file, not this wiki page.

I built my first computer at twelve, long before I understood what the word "engineer" really meant. In the mid-80s, living in the Caribbean with no Radioshack in sight, I scavenged what I could. My father's discarded work computers became organ donors. I pulled copper wires from broken radios, melted solder from old cassette decks, and pieced together a machine that worked and felt alive. I felt driven by curiosity. I wanted to see what I could make next. Then, acceleration hit. I became a teen in the mid-80s, as music changed and MTV let us know about it. New technologies arrived as PCs started to enter every home. Letters that took days or weeks to arrive became faxes. We made mixtapes from albums we couldn't skip through. Satellite TV brought global news into our living rooms, breaking the rhythm of local papers and evening broadcasts. Change felt steady and exciting. I immersed myself in nuclear physics and robotics. Then the internet arrived in the 90s with dial‑up modems, bulletin board systems, and the first steps toward a connected world. As soon as Tim Berners Lee introduced us to it, I learned HTML and launched an advertising business creating websites for retail companies, all desperate to get noticed on this modern platform of the World Wide Web. Email quickly went from a specialist tool to an everyday communication. I created early email databases for retail brands and started doing email marketing with linked web pages, a novelty at the time. By the late 90s, Macromedia Flash exploded onto the scene, and suddenly static sites gave way to interactive experiences. Living in Paris, I got excited about the possibilities. I created brand experiences and games with these new abilities. Experiments filled the internet. Coding languages matured and application builds became simpler at that time, allowing my friends and me to create a platform for fashion houses that helped them all the way from atelier to points of sale for their garments. This introduced me to the startup world. During the dot‑com surge in France, I moved from experimenting to building systems people relied on. The pace of change during those years increased sharply. With one company, whose tech I built—an early version of what later the industry called a social graph—we walked into an American bank in Paris for a meeting in the morning and walked out that same afternoon with a million-dollar investment. Only a few years earlier, I had helped write business plans that sprawled into massive 60-page documents. If you entered a room with anything shorter, nobody took you seriously. Suddenly, the 60-page plan became a punchline. Investors wanted 20-page decks with few words, soon after, 10-page, and now only a summary. As information multiplies, society tries to shrink it. Social media consumed us as the century turned. Our days began with scrolling through endless feeds, each update arriving faster than the last. The more information we had to consume, the shorter it needed to become. Enter the 140-character tweet and the 6-second Vine video. We didn't slow down; we cut everything down to fit the pace of the world. Web 2.0 intensified this, introducing dynamic, data-driven websites. I felt this acceleration through tabs piling up across my browser faster than I could process them. Things accelerated outside the digital world as well. Accessing and creating materials became less expensive and more accessible, so products became cheaper and easier to make. We saw more and more products building up on rapid delivery platforms like Amazon. Services like Kickstarter and Indiegogo came onto the scene as the mythos of the garage creator, like Steve Jobs and Steve Wozniak, became something that everybody could access. In that time, the 2000s, I moved from engineering and entrepreneurship to design and project management. I worked with enterprise companies as they transitioned from fighting for digital real estate to channelling the vast powers of the internet into productivity and innovation. Then came the Smartphone – a computer in your pocket. With this transition, I also moved from the staid prognostication of project management into the agile leadership of product ownership. I found innovation everywhere. The range of ideas and industries felt intoxicating. I led a team building a machine-learning platform for analysing DNA in the wake of the Human Genome Project and another at a global market research company, Kantar, that wanted to have a system that automatically created a human narrative from qualitative interview data. Teaching became part of my rhythm; every time I learned something well enough, I taught it, and the teaching sharpened my learning even further. Product ownership/management swallowed me whole. I taught hundreds of PMs at the hip and rapidly expanding vocational tech school General Assembly. Then at UCLA Anderson, BCG Digital Ventures and eventually through my own technology studio in the US Bank Tower in Downtown Los Angeles. I simultaneously continued working with large enterprises as they struggled to keep pace, helping transform technology teams at places like Sony Pictures, Nike, and NBCUniversal. My tech studio, part coworking space, part incubator/accelerator, part hardware lab, filled with people wandering in from careers in Hollywood and elsewhere with new ideas. We helped them turn those ideas into companies. At this time, the gig economy emerged. Uber appeared everywhere. Bird scooters materialised overnight. Entrepreneurship felt like a global fever. Then came the real acceleration: AI. By this point, my days revolved around helping teams and founders keep pace with the speed of new ideas. I launched my own company, building AI that could recognise human feelings better than a human could and sold it before the real awakening: generative AI. In 2020, the world moved to Zoom in two weeks, and the office all but died. Classrooms became online networks overnight. mRNA vaccines arrived in months rather than years. In 2018, GPT-1 emerged with 117 million parameters, known only to insiders (the first Large Language Model). Then GPT-2 with 1.5 billion parameters barely held coherence. When GPT-3 arrived in 2020 with 175 billion parameters, it changed the tone of the conversation. When ChatGPT began passing professional exams, the speed of change snapped into focus. That speed defines this moment: acceleration at personal, business, societal, governmental, and species levels. My own life traces this arc. I watched each shift, built inside them, and tried to help others adapt to them. If we don't shape the world to absorb these changes, we risk clinging to structures as rigid as the old 60-page business plan, systems built for a world that no longer exists. I've moved through four decades of acceleration, long enough to watch the world rewrite whatever I thought I knew. Nothing stays fixed. The moment you feel certain, you've already fallen behind. I learned early that staying curious, asking questions, and learning faster than the ground shifts kept me relevant. But AI has now deconstructed even that. The concept of "expert" itself collapses when machines can access, synthesise, and generate insights from the entire corpus of human knowledge in seconds. Expertise used to mean accumulating knowledge over decades. Now it means knowing how to learn, unlearn, and relearn faster than the systems around you evolve. Any "experts" I meet want to sell me their certainty, the thing AI has made worthless. I keep learning, not to become an expert, but because learning remains the only thing that survives the acceleration. The innovations I currently bring to life vary as much as they did in the dot-com era. As director of AI at Artium.ai, I accelerate medical innovation at the Mayo Clinic, change culture with Red Bull, and even change how major banks relate to customers. My teams build agentic platforms and smart systems that talk to each other across the globe without human intervention. These technologies have forced companies to evolve into platforms characterised as flexible, dynamic, and continuously updated. We need to extend that mindset to our societies, governments, and personal lives. Our children may have many careers or none at all. Their lives will require adaptability, not a fixed identity. Preparing for this world means learning to think like a platform: fluid, resilient, rebuildable. Forget embracing change, we need to pursue it. Aggressively. During my day, I create these platforms with more and more ability and higher and higher autonomy. I create the machines that replace both human cognitive and physical labour. This has led me to start to think more and more about what happens when this job replacement accelerates. As with my teaching, to help me think, I need to share and get feedback. So I write. I share. And then I write more. And beneath all of this sits a simple truth: as the job markets shrink, we must rethink how people access the resources they need to live. How do we redistribute wealth when few people have jobs? As technology drives down the cost of energy and resources, we must rethink how economies work. What happens when energy costs reach near zero? These questions matter, and their answers will arrive whether we prepare for them or not. This book doesn't claim to answer every question. It offers paths through the transition, ways to reduce harm, and tools to think differently. Cultural differences, assumptions, expectations, and histories all shape how societies respond to the forces of change. We cannot ignore this diversity. The challenge feels large, but the steps can remain small. What matters is that we take them now. Yet as I write this, I recognise something uncomfortable: I have defined myself entirely through what I build, teach, and create. Every decade, every role, every shift became who I thought I had become. My career swallowed my identity whole. The irony doesn't escape me that I argue in this book for systems to change while I write my own sense of self trapped in the old model. Surviving the changes ahead start with changing our mind.