To the person holding this book:
Welcome. I’m glad you’re here.
I want to start by telling you something I don’t say often enough in a classroom: the fact that you enrolled in this course — or picked up this book — is not a small thing. You made a decision to be uncomfortable on purpose. That’s rarer than it sounds. Most people wait until the discomfort finds them.
Let me tell you where we are.
We are, right now, at one of those genuinely rare inflection points in economic history. Not a trend. Not a hype cycle. An inflection point — the kind that splits a timeline into before and after. The steam engine was one. Electrification was one. The internet was one. This is one. And unlike those previous revolutions, which took decades to ripple through the economy, this one is moving at software speed. That means years, not generations.
Here is what that means for you, practically: the gap between people who understand AI and people who don’t is widening faster than at any prior moment in your career. And — this is the part I need you to hear — the gap is not technical. It is conceptual. The people who win in the cognition economy are not the ones who know how to train a model. They are the ones who understand how to think with one.
That is what this course is about. That is what this book is about.
I’ll be honest with you about what this course will demand. It will demand that you stay curious when things feel abstract. It will demand that you do the exercises — not read them, do them. Every chapter ends with something actionable. If you skip those, you are reading about swimming while standing on dry land. The exercises are the water. Jump in.
It will also demand that you let go of a particular kind of intellectual safety — the kind where you wait to understand something fully before you engage with it. AI systems are probabilistic. They are creative. They are sometimes wrong in ways that sound very confident. The people who thrive with them are people who can hold uncertainty comfortably, test quickly, and iterate. If that sounds like startup thinking, that’s because it is.
Most importantly, this course will demand that you stop thinking about AI as a tool you use and start thinking about it as a capability you design around. That is a significant cognitive shift. It will not happen on day one. But by the end of this course, if you do the work, it will happen.
Here is what I can promise you in return.
By the end of this book, you will understand what an LLM actually is — not the marketing version, not the fear-mongering version, but the real mechanistic picture. You will be able to build a working AI setup from scratch. You will know the difference between prompting, engineering, and architecture — and why that distinction matters enormously in practice. You will have built something real: a workflow, a sub-agent, a memory system, something that did not exist before you made it.
You will leave this course operating at a level that most people in your organization — including many of your managers — have not yet reached. That is not arrogance. That is preparation.
One last thing.
I’ve been teaching at the intersection of technology and business for a long time. I’ve watched students arrive skeptical of the hype and leave as convinced practitioners. I’ve watched the opposite, too — students who came in convinced and left humbled by the real complexity. Both outcomes are fine. What is not fine is leaving unchanged.
I wrote this book the way I teach: directly, without hedging, with no patience for content that wastes your time. Every chapter is designed to be finished at lunch. Every concept is explained in business English before it’s explained in technical terms. Every exercise produces something you can use.
Come ready to think. Come ready to build.
Let’s get to work.
— Dr. Ernesto Lee
Florida Atlantic University
College of Business