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Y Combinator

We help founders make something people want. The Y Combinator Podcast is where builders talk about building. From the earliest days of an idea to scaling a company that changes the world, YC partners and founders share real stories, lessons, and tactics from the frontlines.

In this episode of the Main Function Garry sits down with Eric Ries, author of "The Lean Startup", about his new book, "Incorruptible: Why Good Companies Go Bad And How Great Companies Stay Great". Ries breaks down why shareholder primacy often leads to company and product degradation, how founders can lose control of the companies they build, and what legal structures and governance models can protect a company's core mission from outside threats.

How The Best Companies Defend Against Mediocrity And Rot

Paul Graham is a co-founder of Y Combinator. He's funded and mentored companies like Dropbox, Airbnb, DoorDash, and thousands of others through YC, and is one of the most influential voices in the startup world.

In this talk at our YC | Stockholm event last month, Paul walks through why ambitious founders should move to Silicon Valley at least briefly, what makes it uniquely valuable — from serendipitous meetings and faster investor decisions to a deeply embedded pay-it-forward culture — and why returning home afterward may be one of the most powerful things a founder can do to help their local ecosystem, using Stockholm as a case study for what it would take to become the Silicon Valley of Europe.

Paul Graham: Should you move to Silicon Valley?

We're entering a new era of software where a single person, working with AI agents, can build products that previously required entire teams.In this episode of Lightcone, the hosts break down the rise of AI coding agents, "tokenmaxxing", and the emerging workflows behind tools like Claude Code and OpenClaw. They discuss why AI systems today feel less like productivity tools and more like collaborators, why the future of AI should be personal and user-controlled, and how founders are starting to build software in completely new ways.

Tokenmaxxing: How Top Builders Use AI To Do The Work Of 400 Engineers

A 7-million parameter model outperforming models a thousand times its size on tasks like ARC Prize. That's what recursive reasoning unlocks.In this episode of Decoded, YC's Ankit Gupta and Francois Chaubard break down two recent papers on recursive AI models, HRMs and TRMs, that are achieving state-of-the-art results with a fraction of the parameters of today's largest models.They explain why standard LLMs hit a fundamental ceiling on certain reasoning tasks, how recursion at inference time gives small models the compute depth to break through it, and what happens when you combine these ideas with the power of large-scale foundation models.

Beyond Bigger Models: Recursion As The Next Scaling Law In AI

Demis Hassabis 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 Google DeepMind, 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 Garry Tan 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. Chapters:00:00 — Intro00:46 — Demis Hassabis: From Chess Prodigy to DeepMind01:48 — What’s Missing Before We Get To AGI?03:36 — Why Memory Is Still Unsolved06:14 — How AlphaGo Shaped Gemini08:06 — Why Smaller Models Are Getting So Powerful10:46 — The 1000x Engineer12:40 — Continual Learning and the Future of Agents13:32 — Why AI Still Fails at Basic Reasoning15:33 — Are Agents Overhyped or Just Getting Started?18:31 — Can AI Become Truly Creative?20:26 — Open Models, Gemma, and Local AI22:26 — Why Gemini Was Built Multimodal24:08 — What Happens When Inference Gets Cheap?25:24 — From AlphaFold to the Virtual Cells28:24 — AI as the Ultimate Tool for Science30:43 — Advice for Founders33:30 — The AlphaFold Breakthrough Pattern35:20 — Can AI Make Real Scientific Discoveries?37:59 — What to Build Before AGI ArrivesApply to Y Combinator: https://www.ycombinator.com/applyWork at a startup: https://www.ycombinator.com/jobs

How to Build the Future: Demis Hassabis

Replit is the leading no-code app builder for consumers and enterprise, letting anyone with an idea build real, deployed software using natural language. The company just raised a $400 million Series D at a $9 billion valuation.In this episode of Founder Firesides, co-founder and CEO Amjad Masad sat down with YC's Andrew Miklas to talk about Replit's 10-year journey from browser IDE to vibe coding platform, why the people getting the most value aren't traditional developers but founders and domain experts closest to the problem, and what Agent 4 unlocks with parallel agents, built-in design, and the ability to run your entire company on Replit.

The $9B Startup That Wants to Create a Billion New Developers

AI isn't just making teams more productive. It's changing how companies should be built.

In this episode of Startup School, YC Partner Diana Hu explains what it means to build an AI-native company, where AI isn't just a tool but the operating system your company runs on.

She breaks down how to make your company queryable so agents can improve across every function, why management hierarchies break down when an intelligence layer replaces human middleware, and why early-stage founders have a massive edge in building this way from day one.

The Playbook For Building An AI Native Company

Even the most successful websites eventually need a redesign. Take Stripe for example. After six years with the same homepage, they recently unveiled a brand new site that reflects how the fintech giant has evolved over the past few years. So when is the time right for a new landing page? And what should you prioritize in the redesign? In this episode of Design Review YC’s Aaron Epstein sat down Stripe’s Head of Design Katie Dill to pull the curtain back on their high profile redesign and to discuss how their team is evolving in a world dominated by new AI design tools.

Stripe Head of Design Katie Dill Breaks Down Their New Website

Physical Intelligence is building a foundation model that can control any robot to do any task — what the team describes as the GPT-1 moment for robotics.

The company's cross-embodiment approach trains across many different robot platforms, and recent results show tasks being performed zero-shot that last year required hundreds of hours of data collection.

In this episode of The Lightcone, co-founder Quan Vuong sat down with Garry, Jared, Diana, and Harj to talk about why robotics is finally ready for its scaling moment, how PI runs its models in the cloud rather than on-device, and the playbook for what Quan sees as a Cambrian explosion of vertical robotics companies.

The GPT Moment for Robotics Is Here

1 in 11 babies born in America this year will be screened by a genetic test that didn't exist a decade ago.Biotech startup BillionToOne turned a simple but radical idea—detecting rare fragments of fetal DNA in a mother's blood—into one of the most widely used prenatal tests in the U.S. And they're not stopping there. The same approach could unlock something even bigger: early-stage cancer detection from a blood test, a breakthrough that could one day save millions of lives.In this episode of Hard Tech, YC's Jared Friedman sits down with David Tsao and Oguzhan Atay to hear how they went from half a lab bench to a $4B biotech company—and why they believe this is just the beginning of what their technology can do.

This Startup Wants To Catch Cancer Before It Spreads

In this episode of The Lightcone, we talk with Mukund and Madhav Jha, the founders of Emergent - an AI platform that lets anyone build and ship production-ready software. In just eight months, users have created more than 7 million apps on Emergent, with the number doubling in just the last 45 days. We discuss how they built one of the most powerful AI coding agents, why they focused on non-technical users and what it's like building in India for a global audience.

Apply to Y Combinator: https://www.ycombinator.com/apply

Chapters:

00:00 - Intro

01:06 - What Is Emergent?

01:18 - Founder Backstory

02:09 - From AI Testing to General Coding Agents

02:52 - Getting Ahead of the Market

04:18 - The Pivot to Non-Technical Users

05:22 - Why Second Movers Can Win in AI

09:04 - Building for Production, Not Just Prototypes

18:21 - Live Demo: Building Apps with Emergent

24:40 - How Emergent Hires and Runs a Lean Team

29:04 - Is SaaS Dead? The Rise of Personalized Software

34:04 - The Future: Niche Apps, Solo Builders and AI Agency

Building A Global AI Startup From India

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