Antoine Buteau

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Lessons from Balaji Srinivasan

Balaji Srinivasan, a former Coinbase CTO, proposed the Network State: a plan for groups to fund territory and seek diplomatic recognition. His ideas ask how cryptography, pseudonymity, decentralized tech, and startup culture could reshape society and institutions.

Lessons from Evan Spiegel

Evan Spiegel, co-founder of Snapchat, made deletion the default to make digital messages resemble spoken conversation. His decision to reject buyouts and focus Snap on augmented reality and camera hardware frames product conviction and software limits.

Lessons from Jason Lemkin

Jason Lemkin founded EchoSign and built SaaStr into a major community for software founders. His benchmarks for scaling a SaaS company from zero to $100 million in recurring revenue translate growth stages into concrete operating guidance for founders.

Lessons from Brian Armstrong

Brian Armstrong co-founded Coinbase to simplify buying and storing cryptocurrency, then argued for an apolitical workplace focused on product. His experience connects infrastructure scaling, leadership under stress, and the boundaries companies set around mission.

Lessons from Lex Fridman

Lex Fridman, a computer scientist, studies human-AI interaction and autonomous systems while hosting long-form interviews with engineers, scientists, historians, and athletes. His work examines technology, discipline, and human nature to identify durable operating principles.

Lessons from Rodney Brooks

Rodney Brooks, co-founder of iRobot and Rethink Robotics, builds robots while challenging AI assumptions. His work on subsumption architecture, automation, and tracked predictions asks why physical robots remain harder than software and human-like thought stays distant.

Lessons from Denny Zhou

Denny Zhou, a Google DeepMind research scientist and founder of its Reasoning Team, helped author Chain-of-Thought prompting. His work examines how generating intermediate steps can move language models beyond simple text prediction toward structured problem-solving.

Lessons from Sergey Levine

Sergey Levine, UC Berkeley professor and Physical Intelligence co-founder, studies how robots learn through trial and error rather than rigid programming. His research asks if reinforcement learning, offline data, and physical interaction can produce machine intuition.

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