Jeremy Allaire (@jerallaire) is the Chairman, CEO, and co-founder of @circle, the issuer of USDC — a stablecoin with nearly $80 billion in circulation and a core piece of the broader stablecoin market, which has grown from zero to more than $300 billion over the past decade. In this fireside, YC Visiting Partner @nemild sat down with Jeremy to talk about Circle's founding vision of building an internet protocol for dollars, the wave of institutional and regulatory adoption now reshaping the financial system, and why agentic economic activity, not just consumer payments, might represent the most transformative frontier for stablecoin builders in the years ahead. 00:00 - Why Stablecoins Matter 01:45 - Circle's Origin 07:10 - Top Use Cases for Builders Today 11:22 - Consumer vs. Business Adoption 13:20 - Banks & Institutions Enter the Space 17:54 - Global Regulation Landscape 22:40 - AI Agents & the Agentic Economy 26:15 - Missing Infrastructure for Builders 27:38 - Three Big Predictions for Stablecoins

Paul Graham (@paulg) whether founders should move to Silicon Valley, and what it takes to build a startup hub anywhere else. Live from our YC | Stockholm event on April 29, 2026. 01:01 – Why the Big Center Matters 02:45 – The Power of Serendipitous Meetings 04:36 – Investors Move Faster in the Valley 06:03 – Respect Follows the Move 07:59 – The Dropbox Story 09:10 – Measuring Yourself Against Big Fish 12:21 – Silicon Valley's Pay-It-Forward Culture 15:36 – How to Help Stockholm Thrive 17:24 – YC as the Optimal Path 19:54 – Could Stockholm Become The Silicon Valley of Europe?

Demis Hassabis (@demishassabis) has had one of the most extraordinary careers in tech. He started as a chess prodigy and video game designer at 17 before getting a PhD in neuroscience and going on to found DeepMind. His lab cracked Go, solved protein structure prediction with AlphaFold, and then gave it away free to every scientist on earth. That work won him the 2024 Nobel Prize in Chemistry. Today he leads @GoogleDeepMind, pushing toward the same goal he set as a teenager: AGI. On this special live episode of How to Build the Future, he sat down with YC's @garrytan to talk about what still needs to happen to get us to AGI, his advice for founders on how to stay ahead of the curve, and what the next big scientific breakthroughs might be. 01:48 — What’s Missing Before We Get To AGI? 03:36 — Why Memory Is Still Unsolved 06:14 — How AlphaGo Shaped Gemini 08:06 — Why Smaller Models Are Getting So Powerful 10:46 — The 1000x Engineer 12:40 — Continual Learning and the Future of Agents 13:32 — Why AI Still Fails at Basic Reasoning 15:33 — Are Agents Overhyped or Just Getting Started? 18:31 — Can AI Become Truly Creative? 20:26 — Open Models, Gemma, and Local AI 22:26 — Why Gemini Was Built Multimodal 24:08 — What Happens When Inference Gets Cheap? 25:24 — From AlphaFold to the Virtual Cells 28:24 — AI as the Ultimate Tool for Science 30:43 — Advice for Founders 33:30 — The AlphaFold Breakthrough Pattern 35:20 — Can AI Make Real Scientific Discoveries? 37:59 — What to Build Before AGI Arrives

Inference Chips for Agent Workflows @sdianahu Most AI chips are designed for "prompt in, response out." Agents don't work that way. They loop, branch, and hold context across dozens of steps, and current GPUs hit 30–40% utilization as a result. That gap is where purpose-built silicon wins.

Lilac (@LilacML) is an open-source tool that ensures your data scientists always have enough GPUs for their work. They seamlessly connect compute from any source, on-prem or cloud.