Mike Krieger, a former CPO at Anthropic, details his transition to an IC role to build directly with AI, advocating for "unreasonable" asks like porting entire codebases. He shares lessons from Instagram on scaling and highlights Anthropic's internal use of Claude as a proactive teammate, flexible lab structure, and critical insights on AI product design, vertical applications, and mental health in the fast-paced AI industry.
Paul Copplestone, CEO of Supabase, discusses the company's rapid rise as a leading dev tool. He explains their strategic bet on open-source Postgres, the pivotal "Open Source Firebase" rebrand, and how three distinct "chapters" of AI — from vector databases and code generation to advanced AI agents — have dramatically accelerated Supabase's growth and forced a re-evaluation of developer experience and internal operations.
GitHub COO Kyle Daigle discusses the new era of AI agents from the inside. He covers how he uses AI for leadership, the shift from "mega-skills" to "micro-skills," and how GitHub is navigating a 14x growth in commits. The conversation goes deep on the evolution of Copilot, the future of PRs in an agent-driven world, the challenges of scaling, and Microsoft's vision for an ambient AI operating system.
Brian Halligan, HubSpot co-founder and Sequoia's in-house CEO coach, shares his frameworks for building and scaling tech companies. He details his LOCKS framework for evaluating founders, offers tactical advice on hiring "spiky" talent over consensus picks, and discusses the future of go-to-market strategies in the age of AI.
Michael Truell, CEO of Cursor, discusses the company's rapid growth, emphasizing a strategy of deliberate focus on power users over broad democratization. He shares insights into their unique two-day work trials that test for agency, the technical and relational challenges of out-scaling cloud and API providers, and a talent-first approach to M&A, all while navigating a market poised for its next 'iPhone moment'.
Nvidia CTO Michael Kagan explains how the Mellanox acquisition was key to scaling AI infrastructure from single GPUs to million-GPU data centers. He covers the critical role of networking in system performance, the shift from training to inference workloads, and his vision for AI's future in scientific discovery.