Show Notes
Erik Torenberg, Steve Sinofsky, and Martin Casado speak to Aaron Levie, CEO at Box, about what happens to enterprise software when agents become the primary users. They discuss why coding agents succeed where other knowledge work agents struggle, what abstraction layers mean for the workforce, and how data access and systems of record must change in an agent-first world.
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Joel De La Garza is joined by Dylan Ayrey, co-founder and CEO of Truffle Security, and Feross Aboukhadijeh, founder and CEO of Socket, to discuss one of the biggest shifts happening in cybersecurity: AI models are no longer just finding vulnerabilities—they're exploiting them. As frontier models become increasingly capable of hacking, software security, supply chain attacks, and cyber defense are entering a fundamentally new era. The conversation explores AI-powered hacking, software supply chain attacks, leaked credentials, zero-day vulnerabilities, package manager security, and why the path of least resistance for increasingly autonomous AI systems may also be the most dangerous. They also discuss what enterprises, developers, and the open-source ecosystem need to do to adapt as the gap between vulnerability discovery and exploitation continues to shrink.
Elena Burger and Matt Bornstein are joined by Simon Mo, co-founder and CEO of Inferact, the open-source inference engine powering many of today's most advanced AI applications. Together, they explore how open-source AI evolved from a research project into critical infrastructure, why inference has become one of the most important layers of the AI stack, and what it takes to bring frontier intelligence to developers around the world. The conversation covers vLLM's origins, the rise of open-weight models, why companies increasingly want control over their AI infrastructure, and how open-source inference enables the next generation of AI applications. They also discuss model licensing, the economics of open-weight AI, Kimi K3, distillation, AI infrastructure, and why Simon believes the gap between open and closed models is rapidly disappearing.
Matt Bornstein speaks with Mirendil cofounders Behnam Neyshabur and Harsh Mehta about their vision for building self-accelerating AI. After leading research efforts at Google and Anthropic, the founders started Mirendil around a simple question: what happens when AI systems can meaningfully contribute to their own development? Rather than focusing solely on AI as a tool for productivity, they argue that the most important application may be accelerating scientific and technological progress itself. The conversation explores AI research, scaling laws, automated engineering, scientific discovery, and the challenges of building systems that can improve over time. They discuss the future of AI-assisted research, why they believe scientific progress remains bottlenecked by intelligence, and how more capable AI systems could help unlock advances across medicine, engineering, and the natural sciences.
Yoko Li and Justine Moore speak with Ideogram founder and CEO Mohammad Norouzi about image generation models, design workflows, and the evolving relationship between AI and creative work.
Sarah Wang speaks with Exa cofounder and CEO Will Bryk about building search infrastructure for the AI era.