Y Combinator

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頻道 • 2 個節目

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每兩星期更新

6月19日

Why Domain Experts Are Winning In The Age Of AI

Bryant Chou co-founded Webflow, which today powers around 1% of all websites on the internet. Now he's back in the current YC batch with Ploy, an AI-powered website and marketing platform that doesn't just build your site — it connects to your analytics, CRM, and search console to optimize your marketing while you sleep. In this episode of the Lightcone he explains how he built Ploy to be “anti slop,” how building today compares to his first startup, and why founders with domain expertise are making a comeback.Chapters:00:00 — What Experience Gives You in the Age of AI00:38 — Meet Bryant Chou, Co-Founder of Webflow01:22 — His New Startup Ploy02:47 — Rebuilding the Posterous website From 200803:27 — Rebuilding the Scribd website From 200705:04 — Rebuilding the Auctomatic website From 200706:19 — Rebuilding the Escher Reality website From 201707:11 — 12% of the YC Batch Uses Ploy08:26 — The D&D Theory of Founder Skills10:05 — Democratizing Marketing and Growth10:50 — Live Demo: The Design Slurper13:21 — Your Website Should Work for You While You Sleep14:26 — Integrations, Analytics, and the Marketing Brain17:27 — Ploy's Anti-Slop Engine: 3,500 Curated Design Prompts20:05 — The Andy Warhol Theory of AI22:35 — Webflow Origin Story24:26 — Building in a Competitive Market Then vs. Now26:01 — First Three Months: Webflow 2013 vs. Ploy 202527:17 — What Experience Teaches You That Models Can't28:51 — Will Better Models Kill Products Like Ploy?30:32 — The Competitive Moat of Purpose-Built AI33:01 — Agents as Customers: CLI, MCP, and AEO35:02 — Young Founders vs. Experienced Founders36:36 — The Idea Maze and Cloning Yourself With AI42:37 — The Magnifying Glass MomentApply to Y Combinator: https://www.ycombinator.com/applyWork at a startup: https://www.ycombinator.com/jobs

6月19日

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43 分鐘
6月17日

How To Pick A Startup Idea

Many founders get stuck trying to find the perfect startup idea before they commit. But the perfect idea doesn't exist in the abstract. The only way to find what works is to pick one, go deep, and get feedback from real customers. In this episode of Startup School, YC's Jon Xu breaks down how to choose what to build, "burn the other boats," and go deep enough to practically run your customer's business— and why that depth is what surfaces the better idea underneath.

6月17日

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12 分鐘
6月10日

"The CEO Must Be the Chief AI Officer"

Brex co-founder and CEO Pedro Franceschi believes most people still underestimate how much AI will change the way companies are built. AI isn't just another tool, it's a new foundation for building products, teams, and companies.In this episode of Lightcone, Pedro shares why he thinks we're only months into a platform shift as significant as the invention of electricity, how AI has changed the way he works, and why every founder should be "token maxing" to understand the limits of the technology firsthand.He explains why the CEO needs to be the chief AI officer, how Brex is rebuilding itself around AI, and why founders should rethink what's possible when intelligence is available on demand.

6月10日

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54 分鐘
6月3日

How to Build an AI-Native Services Company

Some of the biggest companies of the next decade won't be software businesses, they'll be services companies like insurance carriers, law firms, and tax practices rebuilt from scratch with AI doing most of the work. In this episode of Startup School, YC Visiting Partner Charlie Warren walks through the playbook for building AI native services companies, covering how to pick a market with the right traits, why variance kills these businesses faster than anything else, and the P&L math that’ll transform your business model.Chapters:00:00 — Intro to AI Services Companies01:01 — Picking the Right Market02:55 — Markets YC Likes Right Now03:43 — The Sam Altman Test04:35 — The Right Founding Team05:28 — Building the Product06:19 — Variance Is the Existential Problem07:08 — The Early Demand Trap07:53 — How to Price AI Services08:41 — The P&L Walkthrough09:33 — AI Operating Leverage10:27 — Don't Buy Your Way InApply to Y Combinator: https://www.ycombinator.com/applyWork at a startup: https://www.ycombinator.com/jobs

6月3日

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11 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
5月27日

How To Build Superintelligence Inside Your Company

Building superintelligence inside a company isn't about adding AI as a feature. It's about making it the operating system the whole organization runs on. In this episode of the Lightcone, we sat down with YC's Pete Koomen to talk for the first time about how he led the effort to build YC's internal agent infrastructure from the ground up. We cover how giving agents unrestricted access to one database changed everything, the self-improving skill loops that get smarter overnight and why he thinks we've arrived at the personal computer moment for AI.Chapters:00:00 — Intro00:39 — YC's AI Stack02:15 — The Finance Team Problem That Started It All05:07 — SQL Access Changes Everything07:20 — One Database to Rule Them All09:14 — Jevons Paradox 10:07 — Denormalizing for Agents (G-Brain)12:15 — The Single-Player Era of Agents14:16 — 350 Tools and a Shared Registry16:24 — Skillify, DRY, and MECE Resolvers18:23 — The Self-Improving Dream Cycle20:26 — The Two-Sentence Pitch Skill23:06 — How Super Intelligence Compounds25:10 — Recording Everything as a Building Layer27:10 — The Shared Organizational Brain29:18 — Trust-Default Culture as a Requirement30:44 — Raising the Floor for New Employees32:35 — Horseless Carriages Essay Explained34:24 — Why Chat Is the Best Interface for Agents36:10 — Garry's List → G-Brain Rewrite38:50 — Just-in-Time Software40:49 — Centralizing vs. Decentralizing AI43:32 — The Personal AI RevolutionApply to Y Combinator: https://www.ycombinator.com/applyWork at a startup: https://www.ycombinator.com/jobs

5月27日

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46 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
5月25日

How The Best Companies Defend Against Mediocrity And Rot

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.

5月25日

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50 分鐘

Make something people want.