The Story of Apple Pay with Jennifer Bailey

Fintech went from a full-blown surge to a near standstill in just two years. At its peak, about 25 percent of all venture dollars were pouring into the category. By late 2022, that number had collapsed to almost zero. In this conversation, a16z General Partner David Haber and Plaid cofounder and CEO Zach Perret unpack what actually happened during that cycle and why the market is heating up again. We explore how the industry moved from the explosive growth of 2020 and 2021 into a deep freeze, and why we are now seeing real momentum return. We also dig into the forces reshaping fintech today: AI’s outsized impact on fraud and underwriting, incumbents finally embracing external software, the renewed importance of deposits, and the rise of embedded finance across entirely new categories. Zach shares how Plaid has navigated these shifts, what the company is building now, and how he sees the next phase of fintech taking shape.

In this episode, we’re sharing a conversation with David George, General Partner at a16z on the firm’s growth investing team. David has been involved in backing many of the defining companies of this era and is now investing behind a new wave of AI startups. This discussion goes deep into how the a16z growth practice operates: how the team hires and develops a “Yankees-level” culture, how investment decisions get made without traditional committees, and how they build long-term relationships with founders years before investing. A major focus is AI. David talks through how the team is investing across the stack and why he believes this period could create some of the largest companies ever built. He also walks through the models that guide his thinking: why markets often misprice consistent growth, what makes “pull” businesses so durable, why many important markets become winner-take-all, and what he’s learned from studying exceptional founders — especially the “technical terminators” he’s drawn to.

What if America tried to eliminate crime instead of just reacting to it? Not with slogans, but with staffing, technology, and strategy scaled to the problem. In this episode, Erik Torenberg speaks with Garrett Langley, founder and CEO of Flock Safety, and Ben Horowitz, cofounder of a16z, about what is happening in the cities that are trying. Flock now works with over 5,000 communities to detect crime, recover missing children, and close cases faster than ever. Ben has been closely involved in Las Vegas, where Flock technology, drones, and community policing have raised clearance rates while reducing use of force. They outline what a real national crime-reduction strategy could look like: solving the police staffing crisis, using intelligence to make policing safer, understanding why clearance rates have collapsed, and how public–private partnerships are filling gaps cities cannot. They also tackle the hard questions around privacy, criminal justice failures, and the hidden role of organized crime in everyday offenses.

Ryo Lu spent years watching his designs die in meetings. Then he discovered the tool that lets designers ship code at the speed of thought: Cursor, the company where Ryo is now Head of Design. In this episode, a16z General Partner Jennifer Li sits down with Ryo to discuss why "taste" is the wrong framework for understanding the future, why purposeful apps are "selfish," how System 7 holds secrets about AI interfaces, and the radical bet that one codebase can serve everyone if you design the concepts right instead of the buttons.

AI models feel smarter than their real-world impact. They ace benchmarks, yet still struggle with reliability, strange bugs, and shallow generalization. Why is there such a gap between what they can do on paper and in practice In this episode from The Dwarkesh Podcast, Dwarkesh talks with Ilya Sutskever, cofounder of SSI and former OpenAI chief scientist, about what is actually blocking progress toward AGI. They explore why RL and pretraining scale so differently, why models outperform on evals but underperform in real use, and why human style generalization remains far ahead. Ilya also discusses value functions, emotions as a built-in reward system, the limits of pretraining, continual learning, superintelligence, and what an AI driven economy could look like.