Inside the AI Revolution: How to Become a 10x Founder
A conversation with Jeff Bussgang, author of the newly released book "The Experimentation Machine"
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I recently had the pleasure of interviewing my colleague Jeff Bussgang, General Partner at Flybridge, Harvard Business School prof and author of The Experimentation Machine. The book is extremely timely for today’s founders; in it, Jeff explains how to use AI tools in pursuit of product-market fit. The fundamental principles are the same as they’ve always been, but founders today can leverage AI tools to get there 10x faster.
Jeff is a particularly good source for understanding this shift, with a ton of hands-on experience as both a founder and investor - and the professorial temperament to guide us through it all.
Below is a summary of our conversation, distilled into insights that I believe will resonate with any founder, whether you’re knee-deep in code or just starting out.
From AI Graduate to VC: Jeff’s Background
Jeff studied AI at Harvard in the late ’80s and wrote an undergraduate thesis on neural networks and natural language processing—no small feat for that era. After graduation, he spent some time at BCG, then Harvard Business School, and ultimately launched two venture-backed startups. Both companies enjoyed significant exits (one went public during the original internet boom).
Eventually, he co-founded Flybridge, a seed-stage venture fund focused on AI-first startups. He still identifies as an entrepreneur at heart—co-founding a venture fund is, as he put it, itself an “entrepreneurial journey.” That founder’s mindset is also evident in his role on the HBS faculty, where he treats teaching much like product management: define a problem (or syllabus), create a solution (class content), and continuously iterate.
The “10x Founder” in the Age of AI
As an AI-focused seed investor, Jeff’s vantage point is both practical and visionary. One of his main observations: founders who truly integrate AI tools into every aspect of their business can become “10x founders.” The concept is borrowed from the idea of the “10x developer,” but Jeff believes the effect now extends to entire leadership teams—regardless of whether they can write a line of code.
The crucial takeaway?
“It’s not that AI will replace founders — it’s that founders who leverage AI will replace founders who don’t.”
If you’re not incorporating modern AI tools into your workflow—be it coding, content creation, customer service, or strategic planning—someone else inevitably will. In a fiercely competitive environment, those who scale faster and adapt more effectively to customer needs tend to prevail.
Why The Experimentation Machine?
On the surface, writing a book on AI in 2025 seems like a game of chasing a moving target. Between the latest model releases and newly minted startups, the landscape shifts daily. Jeff’s approach is to offer timeless strategies—like how to nail product-market fit, develop enduring competitive advantages, and create solid business models—while showing readers how to apply AI today to accelerate and refine those strategies.
His central point: the pace of iteration is skyrocketing, and founders have more powerful tools at their fingertips than ever before. But the fundamentals—identifying a critical problem, building something people truly need, and ensuring strong unit economics—remain unchanged.
The HUNCH Framework for Product-Market Fit
Jeff’s time in the classroom taught him that founders often struggle to quantify product-market fit. So, he developed a handy acronym: HUNCH.
H (Hair on fire): Is your product solving an urgent, “hair-on-fire” problem? If the pain is real, customers will adopt even a minimally viable solution—because they need relief immediately.
U (Usage): Are people actually using the product on a regular basis? Churn is a lagging indicator; usage is a leading one.
N (NPS): Do customers recommend you to their friends or colleagues? If so, you’re onto something.
C (Churn, low): Does your retention hold up over time, or do customers drift away?
H (High LTV/CAC Ratio): You need to ensure your revenue from a customer, over its lifetime, significantly exceeds the cost of acquiring that customer.
These five components collectively measure real traction. Founders often forget the importance of each letter—and investors aren’t shy about noticing gaps.
From Barber Shops to Tech Unicorns: The Bowling Pin Strategy
Sometimes, a startup’s initial market looks too small—like it could never become a billion-dollar business. Yet, Jeff emphasized that many of today’s tech successes started with a narrowly defined audience.
Squire began by building software for barbershops to book customers, which at first glance sounds too niche. However, by nailing that specific market, Squire could refine its product and eventually expand to broader offerings (from bookings to payments to credit). In the process, they tapped into a much larger total addressable market—turning an unglamorous space into a multi-hundred-million-dollar venture.
Toast did the same for restaurants, starting with a simple POS system. Fast-forward, and Toast is public, servicing complex restaurant ecosystems with analytics, staffing, and even financial services.
The takeaway is this: Focus on one “headpin” (the narrow market you can dominate), then leverage your momentum to tackle subsequent pins. If you can delight a small group of users, you build a foundation to evolve into adjacent markets or add new features that multiply your relevance.
Who, What, How: The Core Hypotheses
When founders think about early-stage strategy, Jeff boils it down to the who, what, and how:
Who: Narrow down your ideal customer profile. The more specific the target, the easier it is to stand out and become that “must-have” solution.
What: Articulate what you’re building—ideally something high-value that solves a pressing pain point.
How: Devise a practical go-to-market approach. It’s rarely enough to build a stellar product if you don’t have a plan to get it in front of the right people.
He acknowledges that early founders often want to paint vast, ambitious visions—and investors do want to see that larger opportunity. But without the ability to execute on a narrow segment first, your grand vision may ring hollow.
The “Revenge of the MBA”?
Here’s an intriguing spin Jeff mentioned: AI levels the playing field for non-technical founders. Historically, MBAs or “business founders” had to track down a technical co-founder. But with AI-based coding assistants, just about anyone can piece together a rudimentary prototype, and founders can run experiments and iterate thousands of times faster than ever before.
This means there’s an even greater premium on strategic insight. AI can do a lot, but can’t make up for nuance, judgment, taste and other aspects that are very inherently human.
Quick Tips on Prompting
There is a great section of the book all about prompting - so we covered just a few quick tips. Jeff suggests:
Establish context: Describe who you are, what the situation is, and why you need help.
Give details: Provide relevant background: excerpts from emails, spreadsheets, or meeting notes.
Specify the format of the response: Do you want bullet points, pros and cons, or an action plan? The more you guide the AI, the better its output.
If you find yourself getting superficial answers, prompt the AI to ask you questions. This ensures a deeper conversation and finer-tuned feedback.
Final Thoughts
In talking with Jeff, I was reminded how quickly AI is shifting the entrepreneurial landscape—yet how vital it remains for founders to stay rooted in fundamentals. Ultimately, the best strategy pairs an ability to imagine the long game with a willingness to execute methodically, day by day.
Experiment relentlessly. We’ve never had better, cheaper, faster tools for iteration.
Begin small, stay focused. A narrow initial market can be the launchpad for major growth.
Use AI effectively. Don’t underestimate how much time you’ll save—and how quickly your market will move on if you lag behind.
If you’re looking for deeper frameworks or real-world case studies, order Jeff’s new book, The Experimentation Machine, and use code FLYBRIDGE20 for 20% off.
Founder thinking about or gearing up to fundraise? Join us on April 8 for our semi-annual Startup Fundraising Summit. Request an RSVP on the event page.
Startup Fundraising Summit - By Investors, For Founders
Kickstart Your Fundraise with the Startup Fundraising Summit!
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The Agenda
2:30 PM – Check-in & Founder Networking
Kick off the event by connecting with fellow founders and investors.
3:00 PM – Both Sides of The Table
Fundraising insights from people who have been both investors and founders.
Sanjiv Sanghavi – Co-Founder & CEO of Texture, Former Co-Founder of ClassPass, Former VC at Day One Ventures
Lindsay Kaplan - Co-Founder Chief, Investor at Next Wave NYC
Brett Martin – VC at Charge Ventures, Co-Founder of Kumospace, Former Co-Founder of Switch & Sonar, Adjunct Professor at Columbia
4:00 PM – Preparing to Fundraise: Top Legal Considerations
with Neil Toomey (Partner, Gunderson Dettmer)
Neil has been a trusted legal partner to startups and venture funds in the NYC tech ecosystem.
4:30 PM – Understanding the Fundraising Process
with Chip Hazard (General Partner, Flybridge Capital)
Chip is a seed-stage investor backing founders shaping the AI-powered future. Flybridge Capital has over $1 billion under management across six seed funds and nine network funds.
5:30 PM – Unblocking Your Fundraising Process
A tactical session focused on overcoming common fundraising challenges, featuring:
Kendra Schultz – Investor at Benchstrength
Lauren Reeves - Investor at MGV
Morgan Blumberg - Investor at M13
Bryce Johnson - Investor at Primary Venture Partners
6:15 PM – 8:00 PM – Investor & Founder Networking Reception
Meet and connect with 20+ VC and angel investors over drinks and conversation
Love it, thanks for sharing, Dorothy and Jeff!