Y Combinator

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頻道 • 2 個節目

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5月13日

Paul Graham: Should you move to Silicon Valley?

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.

5月13日

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22 分鐘
5月8日

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

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.

5月8日

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41 分鐘
5月1日

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

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.

5月1日

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38 分鐘
4月25日

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

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.

4月25日

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39 分鐘
4月29日

How to Build the Future: Demis Hassabis

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

4月29日

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41 分鐘
2月21日

The AI Agent Economy Is Here

With the takeoff of OpenClaw and MoltBook, a new agent-driven economy is taking shape. In this episode of the Lightcone, we took a look at the explosive growth of AI dev tools and whether the time has come for builders to make something agents want.

2月21日

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23 分鐘
03/12/2025

What Founders Have To Unlearn To Become Great CEOs

Spenser Skates has spent more than a decade building Amplitude from a YC startup into a public company, and in that time, he's had to reinvent himself just as much as the product.Joining the Lightcone pod, he talks through the shift from founder to large-company CEO, the skepticism his team initially had toward AI, and the moment they realized the next wave of analytics would require a full reset.He walks through the hard reorganizations, the bottom-up experiments, and the mindset changes that let Amplitude move fast again.

03/12/2025

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44 分鐘
2月27日

The Fastest Path To Super Intelligence

Poetiq is a new startup founded by former DeepMind researchers that recently achieved a major jump on the ARC-AGI and Humanity's Last Exam benchmark by layering a recursive self-improvement system on top of existing models. In this episode of Lightcone, Poetiq's Founder & CEO Ian Fischer joined us to discuss how small teams can build “reasoning harnesses” that outperform base models, what that means for startups and why automating prompt engineering may be one of the most powerful levers in AI today.Chapters:00:00 – Intro00:40 – What Is Poetiq?01:07 – Recursive Self-Improvement Explained02:07 – The Fine-Tuning Trap02:59 – “Stilts” for LLMs03:14 – Recursive Self-Improvement vs. Fine-Tuning05:05 – Taking the Top Spot on ARC-AGI06:37 – Beating Claude on Humanity’s Last Exam08:40 – How the Meta-System Works10:26 – Beyond RL: A New S-Curve11:32 – Automating Prompt Engineering13:37 – From 5% to 95% Performance14:50 – Early Access & Putting Your Agent on Stilts16:17 – From YC Founder to DeepMind Researcher18:29 – Advice for Engineers in the AI EraApply to Y Combinator: https://www.ycombinator.com/applyWork at a startup: https://www.ycombinator.com/jobs

2月27日

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20 分鐘
4月24日

The Playbook For Building An AI Native Company

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.

4月24日

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10 分鐘
4月16日

The GPT Moment for Robotics Is Here

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.

4月16日

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49 分鐘

Make something people want.