TL;DR: AI and ML founders face the fastest obsolescence cycle in modern business. The model you trained two years ago is a curiosity. The company you founded eighteen months ago has been overtaken by three competitors and an open-source release. The thing that survives this churn isn’t your product. It’s your thinking, and the only place that thinking lives outside your head an AI book that built authority is in the book you haven’t written yet.
The founders who get permanent positions in this field are the ones with books. More on the executive book process. The ones without books get cycled out and forgotten. The choice is more urgent in AI than in any other category.
If you’re an AI or ML founder, you operate in a field where the rate of change is brutal in ways founders in other categories don’t have to think about. The model that was advanced when you trained it’s no longer advanced. The company you started has six well-funded competitors that didn’t exist when you started. The framework your stack was built around has been deprecated. The thing you spent two years building got reduced to a wrapper around an open-source release that came out last quarter.
This is the field. You know it. The thing you may not have thought about clearly is what survives this churn and what doesn’t. Your code doesn’t survive. Your product doesn’t survive in its current form. Your company may or may not survive. The thing that survives, if anything does, is your thinking. The book is the only place your thinking lives outside your head, and if you don’t write the book, the thinking dies with the company.
This is a survival argument about your professional identity in the longest-running careers in a field that punishes founders who don’t establish themselves beyond their current product.
The obsolescence cycle in AI is not normal
Most industries have an obsolescence cycle measured in decades. A bridge engineer’s knowledge holds for forty years. A surgeon’s training holds for twenty. A lawyer’s framework holds for ten. AI founders operate on cycles measured in months. The model architecture you mastered last year is a teaching example this year. The specific techniques that made your product work are now a chapter in a textbook somebody else is writing.
This means the time you have to establish yourself as a permanent figure in the field is much shorter than it would be in any other category. The window for becoming the person whose thinking outlasts their current product is open for a few years, not a few decades. The founders who use that window to publish are the ones whose names show up in the citations of the next generation. The founders who don’t get cycled out and become footnotes.
What gets remembered in this field
Not the products. Look around. The products from five years ago that everyone was excited about are mostly gone, absorbed, or pivoted into something else. The companies from ten years ago that defined the field have either reinvented themselves three times or disappeared. The thing that’s survived from those eras isn’t the technology. It’s the people whose names you still recognize, and you recognize them mostly because they wrote things down.
Yann LeCun. Geoffrey Hinton. Andrew Ng. Demis Hassabis. The names that stayed permanent in this field are the names of people who published. Not just academic papers, although the papers are part of it. Books, essays, the kind of long-form thinking that survives the technology that triggered it. The technology dates. The thinking, if it’s good, ages.
You’re running out of time to do this. Your current product cycle is one or two more iterations from being obsolete. The window to publish your thinking, while you’re still inside the relevant moment, is closing.
What book does an AI founder need to write?
Not a technical book on your current architecture. The technical book ages out with the architecture. Not a memoir of starting the company, although elements of the founding story belong in it. Not a hype book about how AI will change everything, because that genre is saturated and the credible audience is already saturated with it.
The book that lasts is the book that captures your particular view of how the field actually works, what the patterns are, what most people miss, what you’ve learned about building these systems in production, what you believe about where the field is going, and what specifically you’re arguing for. Strong opinions. Original framing. The kind of thinking that, when somebody reads it five years from now, still feels true even though the specific examples have dated.
This book has the same structural challenge as the book a trade-publishing academic has to write. The argument has to be one that survives its specific examples. The voice has to be one that respects the reader’s intelligence without retreating into the jargon of the field. The thinking has to be substantial enough that it justifies the reader’s time even after the technology in the examples is obsolete.
The window-closing argument
You have a few years in which you’re recognizable to the field as a current voice. Once you stop being current, the window for being read as authoritative starts closing. Your future is one of three categories.
The founder who became the figure. Wrote the book at the right moment, established their thinking in print, became the person whose argument outlasted their company. Continues to be cited, invited, and read decades later, regardless of what their current product is doing.
The founder who scaled their company and became a CEO. Didn’t publish, but the company grew large enough that they became famous as an operator. This is a smaller category than founders assume. Most companies don’t scale to that level.
The founder who got cycled out. Built something interesting, ran into the next wave, didn’t establish themselves beyond the company, and is now hard to find. This is by far the largest category. Not because the founders weren’t capable, but because they didn’t put the work into the long-term identity asset.
Not because the founders were not capable, but because they did not put the work into the long-term identity asset.Share on X
Most AI founders are heading toward the third category. The ones who actively move toward the first do so by writing.
The other reason this matters
You’re competing for capital, talent, and partnerships every year of the company’s life. Every one of those conversations is mediated by your visibility outside the company. The investor doing the second round wants to know what you think about the field, not just about your product. The senior engineer evaluating offers wants to know whether you have a view, not just a deck. The enterprise customer wants to know whether you have authority in the category, not just a feature set.
The book is the asset that establishes all three. Without a book, you’re one of many founders pitching similar narratives. With a book, you’re the founder whose thinking is durable enough to be read in print. The difference shows up in the quality of the deals you close, the people you can hire, and the partnerships you can secure.
The 2024 study on business book ROI from Amplify, Gotham Ghostwriters, Smith Publicity, and Thought Leadership Use found median ghostwritten book revenue of $92,500 and four-times-higher profitability than self-written books. AuthorROI.com has the data. For AI founders, the deal-level effects on capital raised and talent attracted are typically larger than the direct book revenue by orders of magnitude.
What objection do most AI founders make?
“I don’t have time. I have a company to run.”
You also have a personal identity to build that survives the company. The company is one of many you might be associated with across the next thirty years. The book is the asset that connects all of them under your name as a recognizable figure in the field. Founders who skip this step have to rebuild credibility from zero with every subsequent venture. Founders who did the book have credibility that compounds.
The time investment isn’t trivial. The work is real. The interviews and the writing and the editing and the review take months of attention. The math, however, runs strongly in favor of doing it now instead of later. Now, while you’re inside the moment your thinking is most current. Later is the answer that produces the third category outcome above.
What to do this week
If you’re an AI or ML founder and you’ve been thinking about a book in some background way, the conversation to start is about what your argument actually is, what your particular thinking captures that nobody else’s captures, and what the book has to be to outlast your current product cycle.
The book on this: The Day Your Website Died is forty-two chapters on how answer engines decide who gets named, and what to do about it.
The Book Discovery Intensive is built around that. The work session approach is suited to founders who don’t have time to develop the book themselves and need a structured way to extract the argument from working interviews. Book the call if that’s useful. The case studies page shows what this has produced across professions.
The window closes faster than most AI founders realize. The choice this week is whether you publish while you’re still inside the relevant moment, or after it’s passed.
Frequently Asked Questions
Related: an AI book that built authority