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.

In this episode of Founder Firesides, YC Managing Partner Jared Friedman talks to Karine Mellata, co-founder of Variance (W23), who is coming out of stealth and announcing their $21 million Series A.

Variance builds purpose-built AI agents for risk and compliance — automating fraud detection, content review, and identity verification for Fortune 500 companies and platforms like GoFundMe. They discuss why Variance built in the shadows for three years, detecting state-sponsored fraud rings, and the accident that nearly ended the company.

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

Solugen is reinventing the trillion-dollar chemical manufacturing industry by combining biology and chemistry in a new way. In this episode of Hard Tech, YC's Jared Friedman visits co-founders Gaurab Chakrabarti and Sean Hunt at their Houston HQ to see how they went from a $7,000 PVC reactor to a billion-dollar company competing with industry giants. They cover the breakthrough behind their enzymatic + catalytic production, how they found their first customers, and why starting small and staying close to customers let them win in a capital-intensive industry.

Chapters:00:00 - A New Kind of Chemical Plant01:02 - Fusing Biology + Chemistry In a New Way02:23 - The Eureka Moment: From Pancreatic Cancer to Hydrogen Peroxide03:30 - Using A Sugar Feedstock Over Oil and Gas 04:22 - Proving Enzymes Work at Scale In Chemical Manufacturing05:16 - The $7K PVC Reactor06:44 - Finding First Customers at YC08:12 - What The Co-founders Got Out of YC09:33 - Seed Round to Bio Forge10:32 - Scaling to a Full-Size Plant (Bioforge)11:57 - The Future of American Manufacturing12:29 - The Next Decade of Solugen

Apply to Y Combinator: https://www.ycombinator.com/applyWork at a startup: https://www.ycombinator.com/jobs

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

YC alum Max Hodak is the co-founder of Neuralink and founder of Science, a company building brain-computer interfaces that can restore sight.Science has developed a tiny retinal implant that stimulates cells in the eye to help blind patients see again. More than 40 patients have already received the treatment in clinical trials, including one who recently read a full novel for the first time in over a decade.In this episode of How to Build the Future, Max joined Garry to discuss how BCIs work, what it takes to engineer the brain, and why brain-computer interfaces may become one of the most important technologies of the next decade.

As no-code design tools become more common, so do the pitfalls. You know what they look like - the purple gradients, annoying hover effects, sections that fade as you scroll. So how do you avoid a site that feels vibe coded while still taking advantage of these new tools? In this episode of Design Review, YC’s Aaron Epstein is joined by Visiting Partner Raphael Schaad, the founder and designer of Cron (now Notion Calendar). Together they’ll review user submitted sites with an eye for how to leverage these tools and avoid the common vibe coding mistakes.

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

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.

A very special guest on this episode of the Lightcone! Boris Cherny, the creator of Claude Code, sits down to share the incredible journey of developing one of the most transformative coding tools of the AI era.

In the AI era, startups aren't winning by hiring faster — they're winning by automating as many internal functions as possible. In this episode of Main Function, Garry breaks down how tiny teams are beating companies 20x their size by building automations into every workflow, from engineering to ops to customer support.