Super Founders with Ali Tamaseb & James Currier
In this episode, James Currier converses with guest Ali Tamaseb about his book "Super Founders", discussing the methodology and data collection process. They delve into the impact of socioeconomic diversity among founders, the correlation between success and academic or career history, and the venture capitalism game. Insights on overcoming narrative bias, the value of small failures, and the role of faith and adaptability in venture capitalism are also explored.
Key Points
- Ali Thomasp, a partner at DCVC and author of "Super Founders," reveals that many commonly held beliefs about what drives startup success, such as the importance of a founder's age, educational background, or technical expertise, do not significantly correlate with the likelihood of creating a unicorn company.
- The research shows that the experience of building and selling, regardless of the scale of previous ventures, is a more predictive indicator of future success in founding a billion-dollar company than traditional markers like prestigious employment or academic history.
- Data suggests that while founders from top universities and well-known companies are more represented among unicorn founders, a significant number of successful founders come from less recognized institutions and diverse backgrounds, highlighting that opportunities for success are not limited to elite networks.
What started as a viral medium article from two years ago has now turned into 'Super Founders', a book on what data reveals about billion-dollar startups. Today on the NFX Podcast we have Ali Tamaseb (partner at DCVC) talking with James Currier about his data-driven approach to understanding what really differentiates billion-dollar startups from the rest.
The book includes exclusive interviews with the founders/investors of Zoom, Instacart, PayPal, Nest, Github, Flatiron Health, Kite Pharma, Facebook, Stripe, Airbnb, YouTube, LinkedIn, Lyft, DoorDash, Coinbase, and Square, venture capital investors like Elad Gil, Peter Thiel, Alfred Lin, and Keith Rabois.
Ali Tamaseb has spent thousands of hours manually amassing what may be the largest dataset ever collected on startups, comparing billion-dollar startups with those that failed to become one—30,000 data points on nearly every factor: number of competitors, market size, the founder’s age, his or her university’s ranking, quality of investors, fundraising time, and many, many more.
Chapters
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Transcript
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