Learn how the best startups iterate their way to success and find PMF faster than ever with the power of generative AI.
True to the experimentation mindset, I will be writing and iterating on the content in the coming months.
Subscribe to my newsletter, The Experimentation Machine, to read early excerpts, share feedback, and discover more opportunities to contribute.
I’m excited to announce that I am working on my next book: The Experimentation Machine: Finding Product-Market Fit in the Age of AI.
My goal is to create the essential guide for early-stage founders, offering a systematic, AI-augmented path to startup success. The methodology is based on the popular Harvard Business School course I’ve taught to thousands of students for over a dozen years, Launching Tech Ventures (LTV).
The book will be published at the end of the year.
I am constantly applying the frameworks I learned in Jeff’s course throughout my entrepreneurial journey, which includes launching an AI platform for investors.
Raghu Yarlagadda, co-founder and CEO of FalconX, a digital asset prime brokerage whose most recent financing was valued at $8 billion.
Build Your Startup as an Experimentation Machine
Many startups grapple with the elusive concept of product-market fit, often perceived as a nebulous, intangible “feeling” that only a few founders are lucky enough to stumble onto. This conventional wisdom is simply wrong.
The Experimentation Machine offers a rigorous, structured approach to defining and achieving success by outlining the clear steps that startups can take to transform product-market fit from an abstract concept into a tangible goal—-and how to use AI as a supercharged copilot. It will also feature case studies of real-world startup founders who iterated their way to success.
The main focus of the book will be to help founders define and answer three key hypotheses:
- How to identify a “hair on fire” customer value proposition
- How to build a scalable go-to-market sales and marketing engine
- How to discover and deploy the optimal business model and pricing formula for sustainable growth
- Using AI as a catalyst to test and iterate faster than ever before—almost like having an extra co-founder on your team
Despite some common misconceptions, entrepreneurship—and the precise processes that entrepreneurs execute on their path to success—can be taught.
Although I can’t guarantee a startup’s success, certain techniques—turbocharged by AI—can be applied to the entrepreneurial journey to dramatically improve the chances of winning.
The book is ideal for early-stage (pre-PMF) technology entrepreneurs, but it will also appeal to any startup founder or joiner, business students, and anyone who wants to learn the principles of entrepreneurship.
Alpha Readers Wanted
True to the spirit of the book, I will be running tests throughout the process. To that end, I am looking for ~50 “Alpha Readers” to join me.
Please let me know if you might be open to not only reading the first drafts of the book, but applying the lessons and frameworks to your own ventures and giving me tangible feedback on the concepts and frameworks.
If you are a founder, aspiring founder, or founding team member and interested in joining my Alpha Reader Group, sign up here:
Be an Alpha Reader
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