Y Combinator

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3月27日

How François Chollet Is Building A New Path To AGI

François Chollet has spent years asking a different question than most of the AI world. Instead of scaling what already works, he’s trying to understand what intelligence actually is—and how to build it from first principles. In this episode of Lightcone, he traces that path from his early work on deep learning to the creation of the ARC prize, and the launch of ARC V3, a new benchmark designed to measure something deeper than performance: the ability to learn, adapt, and reason efficiently in entirely new environments. He explains why today’s systems may be hitting limits, what recent breakthroughs really mean, and why reaching true general intelligence may require a fundamentally different approach.00:00 - AGI by 2030?00:31 - Introducing Ndea: A New Path Beyond Deep Learning01:08 - A New ML Paradigm 01:30 - Replacing neural nets with compact symbolic programs03:04 - Why Ndea Isn’t Competing With Coding Agents05:20 - Why Everyone Might Be Wrong About Scaling LLMs07:22 - Why Coding Agents Suddenly Work So Well08:50 - The Limits of LLMs in Non-Verifiable Domains10:48 - What AGI Actually Means (And Why Most Definitions Are Wrong)13:30 - Why Deep Learning Hits a Wall 14:00 - ARC’s Origin Story18:20 - ARC Benchmarks Explained: From V1 to V322:49 - The RL Loop Powering Coding Agents Today27:03 - ARC-AGI V3: Measuring “Agentic Intelligence”31:14 - Inside the ARC Game Studio35:31 - Could AGI Fit in 10,000 Lines of Code?44:01 - Building Ndea: From Idea to Compounding Research Stack46:46 - The Future of ARC: Benchmarks That Evolve With AI47:21 - Why There’s Still Huge Opportunity for New AI Paradigms53:37 - How to Build a Breakout Open Source Project - Lessons From Kera56:39 - Advice For How To Think About AIApply to Y Combinator: https://www.ycombinator.com/applyWork at a startup: https://www.ycombinator.com/jobs

3月27日

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57 分鐘
07/11/2025

How To Recruit The Best Engineers And Sales Reps

Most founders think hiring is about interviewing. But it's actually about selling.For Startup School, Juicebox co-founder & CEO David Paffenholz joins YC's Harj Taggar to share how early-stage founders can find, pitch, and close top engineering and sales talent— from crafting better outreach to winning great hires from Big Tech— even when you're an unknown startup.

07/11/2025

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43 分鐘
30/05/2025

State-Of-The-Art Prompting For AI Agents

At first, prompting seemed to be a temporary workaround for getting the most out of large language models. But over time, it's become critical to the way we interact with AI. On the Lightcone, Garry, Harj, Diana, and Jared break down what they've learned from working with hundreds of founders building with LLMs: why prompting still matters, where it breaks down, and how teams are making it more reliable in production. They share real examples of prompts that failed, how companies are testing for quality, and what the best teams are doing to make LLM outputs useful and predictable. The prompt from Parahelp (S24) discussed in the episode: https://parahelp.com/blog/prompt-design

30/05/2025

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31 分鐘
1月14日

How To Get Your First Customers

When you're starting out, it isn’t enough to just build a minimum viable product. You also need a minimum evolvable product - one that can adapt to the needs of those critical early customers. In this episode of Main Function, YC General Partner Ankit Gupta offers an update to the classic MVP playbook. He’ll outline strategies for getting your first customers, the power of adaptability and how feedback from early users will ultimately shape the future of your product and your company. Apply to Y Combinator: https://www.ycombinator.com/apply Work at a startup: https://www.ycombinator.com/jobs Chapters: 00:00 – The Minimum Evolvable Product 00:46 – Finding the First Believers 01:29 – Counterintuitive Rules To Get Early Users 02:10 – Learn Fast, Don’t Fear Churn 02:52 – How Early Users Shape the Market You Enter 04:22 – Tesla Case Study 05:14 – How To Build To Evolve

1月14日

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6 分鐘
18/06/2025

Alexandr Wang: Building Scale AI, Transforming Work with Agents & Competing With China

Alexandr Wang started Scale AI to help machine learning teams label data faster.It started as a simple API for human labor, but behind the scenes, he was tackling a much bigger problem: how to turn messy, real-world data into something AI could learn from. Today, that early idea powers a multi-hundred-million-dollar engine behind America's AI infrastructure—fueling everything from Fortune 500 workflows to real-time military planning. Just last week, Meta agreed to invest over $14 billion in Scale AI, valuing the company at $29 billion.Alexandr joined us on the Lightcone to share how Scale AI evolved from a scrappy YC startup into the backbone of some of the world's most advanced AI systems, how he thinks about competition with Chinese AI labs, and what it takes to build infrastructure that shapes the frontier.

18/06/2025

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1 小時 1 分鐘
13/04/2018

#69 - Anne Wojcicki of 23andMe and Sam Altman

Anne Wojcicki is the cofounder and CEO of 23andMe, which provides direct-to-consumer genetic testing.Sam Altman is the president of YC Group. He interviewed Anne for a series called How To Build The Future, which you can check out on our YouTube channel.

13/04/2018

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29 分鐘
26/07/2017

#21 - Emily Weiss on the Insights That Grew Glossier - With Amy Buechler at the Female Founders Conference

Emily Weiss is the founder and CEO of Glossier. Amy Buechler is Batch Director at YC. Video and transcript are on the YC blog.

26/07/2017

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27 分鐘
06/09/2018

#93 - Peter Reinhardt

Peter Reinhardt is cofounder and CEO of Segment. Segment helps companies capture data from every customer touchpoint and send it to the tools where it can be used most effectively.They were part of the YC Summer 2011 batch.The YC podcast is hosted by Craig Cannon.***Topics00:26 - What is Segment?1:56 - Segment’s first customers3:31 - Their YC application4:26 - Going through YC5:56 - Realizing their first product didn’t work10:56 - Launching Analytics.js12:11 - Experiencing product market fit17:21 - Debating whether to launch or build out the product19:41 - Evan Farrell asks - You mentioned in the SS lecture that you had to totally pivot to Analytics.js to find PMF, is it possible to purely iterate on something people kinda like to find PMF, or should it be clear from the outset if a new idea is something people want?20:56 - The importance of having a skeptic on your team23:56 - Customer interviews26:56 - Benjamin Liam asks - How did they know they have the right messaging to explain their product?28:26 - Idea generation33:11 - Danny Prol asks - What values and standards do you have in place for your team at Segment? And how do you actively build that culture into your company?37:26 - Ashwin Doke asks - How has GDPR impacted Segment's business model?39:41 - Andrew Pikul asks - Any advice he has on asking for more money than you're comfortable asking for. 42:11 - Juan Carlos Garza asks - How did YC help you to where Segment is right now?43:41 - Juan Carlos Garza asks - In an early stage, what's the thin line between ignoring a customer suggested feature or moving a customer requested feature to the core of your application?45:11 - Biggest learnings since YC45:16 - Important hires at Segment

06/09/2018

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49 分鐘
13/10/2022

What Does It REALLY Mean To Do Things That Don't Scale?

Dalton Caldwell and Michael Seibel talk about Paul Graham's essay "Do Things That Don't Scale" and what it really means for founders. Read the essay here: http://paulgraham.com/ds.html Apply to Y Combinator: https://www.ycombinator.com/apply/

13/10/2022

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19 分鐘
09/05/2018

#76 - Carola Schönlieb

Carola Schönlieb is an applied mathematician at the University of Cambridge. She’s also a Turing Fellow at the Alan Turing Institute and the head of the Image Analysis group at Cambridge’s Department of Applied Mathematics and Theoretical Physics.In this episode we cover mathematical approaches to image processing.The YC podcast is hosted by Craig Cannon.

09/05/2018

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42 分鐘

Make something people want.