Pattern Breakers, written by Mike Maples Jr. and Peter Ziebelman, challenges traditional startup wisdom by revealing the hidden forces that drive extraordinary success. The book is based on extensive research and real-world examples from transformative startups like Twitter, Twitch, and Lyft. It emphasizes the importance of a different mindset and actions to harness developments that others might miss or initially see as crazy. The authors provide practical advice on how to transcend ordinary thinking, capitalize on market opportunities, and build a community of true believers to revolutionize industries.
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Mike Maples knows how AI startups can beat incumbents with billions of dollars.
Mike—who wrote early checks to Twitter, Twitch, Okta, and Lyft, and now invests through Floodgate, the fund he cofounded—told me it's not about the smartest model, or raising the most money.
Startups can win in AI with better strategy.
AI is changing the economics of startups—both how they’re started and how they’re funded. A new breed of companies is emerging, and I invited Mike on the show to talk about how they can best strategize. Last year, Mike co-authored a book called Pattern Breakers, which is essentially a guidebook to why there’s no guidebook to building companies. I really liked it, and my colleague Evan Armstrong reviewed it for Every, so I was glad to have him on. We talk about how shifts in technology create space for smaller players to compete—even with AI giants like OpenAI—and how to capitalize on them.
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Timestamps for Spotify:
Introduction: 00:02:20
Innovate the business model, not just the product: 00:06:02
How startups can compete against the likes of OpenAI: 00:15:49
Mike’s take on DeepSeek: 00:19:34
Why the future has always belonged to the tinkerers: 00:21:44
How small teams today can make big money: 00:24:03
Find niches that incumbents can’t or don’t want to enter: 00:28:55
The qualities of the truly AI-native: 00:47:08
How AI changes the funding model for software companies: 00:53:46
Knowledge work is moving toward systems-level thinking: 00:58:23
Links to resources mentioned in the episode:
AI and I 