Y Combinator
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Demis Hassabis on choosing what’s worth spending your life building in a world changing this fast: “Going after hard problems and deep problems, it’s no more difficult in some ways than going after a shallower, simpler, more superficial problem. They’re just differently difficult.” “Given life’s very short and you only have so much time and energy, you might as well put your life force into something that will really make a difference.” “If you start off on a deep tech journey today... you’re talking about a 10-year journey for true deep tech. So now you have to consider AGI appearing in the middle of that journey.” “Imagine what that world would look like and then build something that would be useful if that comes in halfway through.”
Y Combinator101,159 Aufrufe • vor 1 Tag
Alexandr Wang on what matters in an age of abundant intelligence: “The scarce resource isn’t going to be intelligence or agency. I really think it’s going to be vision and ambition.” “Do you have a clear view of what you want the world to look like in the future? What is the one way in which you wanna put your finger on the scale for how the future of the world will develop?” “AI will make that easier... But the flip side of that is then all of a sudden you can dream bigger.”
Y Combinator254,087 Aufrufe • vor 4 Tagen
Jensen Huang on why founders don’t need to be right from day one, but they do need to be able to learn quickly: “The technology that founded the company turns out to be exactly wrong.” “I went down to Fry’s, and I bought three textbooks... I brought them back to the company. I gave them to the engineers.” “Everybody would have thought that NVIDIA started out as world leaders in 3D graphics. We learned it from a textbook.” “The big lesson for me is technology’s changing all the time. So long as you’re able to confront reality, so long as you are able to learn, the technology itself actually doesn’t matter. Since then, NVIDIA has been inventing all kinds of technology." "We approach everything with the same attitude. If it’s important to do, we’re going to go learn it. How hard can it be? It always turns out to be much, much harder than we expect. But you go into it with the attitude, how hard can it be?”
Y Combinator67,401 Aufrufe • vor 2 Tagen
Halluminate is building reinforcement learning environments and benchmarks to help AI models do knowledge work beyond coding, starting with finance. With a team of fewer than 10 people, the company works with four of the top five closed-source US AI labs and recently raised a $30M Series A. In this fireside, co-founders Jerry Wu and wyatt marshall sit down with YC's Jon Xu to share how testing browser agents led them to building the environments models now use to practice tasks like financial modeling. They explain why better verification, not just more training tasks, is critical to making models smarter, and how that work could eventually lead to simulated companies where teams of AI agents learn to work together. 00:00 — Halluminate’s Pivot From Evals to Training Environments 03:48 — Teaching AI to Do Financial Work 07:13 — Why Verification Matters More Than Volume 10:13 — From Finance to Simulated Companies 13:30 — AI Safety and Building the Team
Y Combinator260,015 Aufrufe • vor 16 Tagen
BioStack (getbiostack) builds simulation environments where healthcare AI models practice on real clinical data. Messy records, lab tests, notes, outcomes unfolding over months— BioStack turns that into a post-training loop: data, evals, rewards, benchmarks. They've grown from six figures to seven figures in revenue in just the last few weeks. Congrats on the launch, Sanat Mishra & Parth Patwa!
Y Combinator2,256,388 Aufrufe • vor 4 Monaten
Kuli (Kuli) is the AI coworker that gives marketers their time back and makes them 10x more efficient. It watches all videos on socials to find the next trend and gets work done. Already live at Fortune 100 brands, it plans and runs their campaigns with creators. Congrats on the launch, Mike Hodara & Jonathan!
Y Combinator2,450,702 Aufrufe • vor 5 Monaten
Harnesses often get dismissed as just scaffolding, just prompt engineering, and not real research. But that couldn't be farther from the truth. The same model weights that score 30% on ARC-AGI score 95% with a better harness. So we gathered a group of researchers and founders working at the frontier to do a deep dive into the state of harnesses. We cover how we got to this point, the case for making your harness as expressive as possible, and what YC learned building an agent for every employee in the company. 00:00 - Francois Chaubard: Why harnesses matter 04:27 - Building an auto-researcher by accident 07:13 - A five minute history of harnesses 13:56 - Self-improving harnesses 18:35 - Seth Karten: Prime Agent, a self-improving RLM harness 21:50 - Context as an L1, L2, L3 cache 24:51 - From Turing machine to von Neumann computer 28:33 - Messaging between agents 30:04 - ARC-AGI results 33:09 - Emulator Bench and GPU kernels 37:30 - Jon Saad-Falcon: OpenJarvis, personal AI on personal devices 38:26 - How far behind are local models 39:21 - The five primitives of a personal AI stack 42:47 - Letting cloud models optimize your local stack 43:53 - 800x cheaper than the cloud 45:58 - Josh France and Regan Bell: QM, YC's agent harness for work 47:29 - A history of YC's internal agents 49:24 - OpenClaw and a fleet of 50 agents 51:04 - Pulling the brain out of the sandbox 54:43 - Letting the agent choose its own sandbox and model 57:16 - The grind tool: budgets on goals 58:50 - Agents don't understand social context
Y Combinator497,048 Aufrufe • vor 1 Monat
Paul Graham on what surprised him most about AI: “The way we thought it was all going to play out was you start out with a perfect fly.” “Instead, what we got was basically a full-on human, but full of shit.” “Instead of starting with perfect and then working your way up to human, you start with human and then work your way towards perfect.”
Y Combinator54,317 Aufrufe • vor 5 Tagen
AI agents will pay you to chat with them. When AI agents hit a wall, Humwork's (Humwork) MCP server connects them to a verified domain expert in 30 seconds. Their experts include senior engineers, marketers, designers, and more. Congrats on the launch, Yash Goenka and Rohan Datta!
Y Combinator1,788,270 Aufrufe • vor 6 Monaten
Since the start of the year, OpenCode (YC W21) — an open source alternative to Claude Code and Codex that works with any model — exploded to 4.6 million weekly active users, 13 million monthly actives, and roughly $40M in annualized revenue. In this episode of The Lightcone, Harj Taggar, Jared Friedman, and Diana talk with Jay V (Jay), OpenCode’s CEO, about what’s driving this wild growth, the Anthropic clampdown that inadvertently fueled it, and the almost 20 year founder journey that led him here. 00:44 — OpenCode’s Explosive Growth 01:16 — 20x Growth, 13M Users, and 7 Trillion Tokens 03:39 — The Anthropic Controversy That Changed Everything 05:43 — Bringing AI Coding Agents to the World 06:39 — When Open Source Models Became Good Enough 08:56 — What Millions of Developers Are Actually Using 13:31 — Why OpenCode Is Huge Outside the US 15:27 — Why Fortune 500 Companies Choose OpenCode 16:36 — The Economics of AI Tokens 20:02 — How Enterprises Are Using Coding Agents 22:58 — AI’s New Unit Economics 24:56 — Why Model Choice Matters 29:55 — The Product Decisions Behind OpenCode 34:21 — A 16-Year Overnight Success 41:16 — Why Jay Never Gave Up
Y Combinator754,967 Aufrufe • vor 2 Monaten
A Cloud for Small Software Pete Koomen Agents make it easy to build personal tools for yourself or your team. But deploying, securing, and sharing that software is still far more complicated than creating it. A cloud built for small software could remove that complexity and make bespoke tools as easy to share with a colleague as a Google Doc.
Y Combinator691,375 Aufrufe • vor 2 Monaten
Jeetu Patel is Cisco’s President and Chief Product Officer, helping turn one of the world’s largest technology companies into what he calls “the world’s largest startup.” Cisco is now positioning itself as the picks-and-shovels company for the AI era, spanning networking, security, silicon, and infrastructure. Its AI infrastructure business went from zero to $9.3B in orders in just two years. In this episode of Main Function, Jeetu joins YC's Jared Friedman to talk about bringing a founder mindset to the company, and what the massive data center buildout looks like from the inside. He also shares the unlikely path that took him from waiting tables at Sizzler to leading product at Cisco, and the lessons he’s learned about ambition, compounding, and making the most of the opportunities in front of you. 00:00 — Cisco’s Bet on AI 03:38 — Running Cisco Like a Startup 06:45 — The Infrastructure AI Agents Need 10:00 — Getting 32,000 Engineers to Embrace AI 14:07 — Bringing AI to Hardware and Silicon 17:15 — Inside the AI Data Center Buildout 21:27 — Are We Overbuilding AI Infrastructure? 25:10 — Building Trust in AI Agents 28:18 — From India to Waiting Tables at Sizzler 32:12 — Choosing Learning Over Ego 35:31 — Ambition, Teamwork, and Compounding 39:31 — Don’t Squander Your Opportunity
Y Combinator68,433 Aufrufe • vor 9 Tagen
🦙 ollama is used by 9 million developers and 85% of the Fortune 500, giving co-founder and CEO Jeffrey Morgan (Jeffrey Morgan) a unique view into which AI models people are actually using and how that’s changing. Right now, the biggest shift he sees is toward open models, driven by coding agents, falling costs, and capabilities that are rapidly catching up to the frontier labs. On Ollama Cloud, that shift has driven a 150x increase in token usage since the start of the year. In this episode of Lightcone Podcast, Jeff joins Garry Tan, Jared Friedman, Diana, and Harj Taggar to talk about the future of open models and the story behind Ollama, from two years of searching for the right idea to building one of the most widely used AI developer tools in the world. 00:43 — The Shift to Open Models 03:03 — How AI Agents Are Driving Token Usage 05:31 — Are Open Models Catching Up? 08:26 — What Happens When a New Model Launches 11:31 — Ollama as an Operating System for AI 14:05 — The New Opportunities Above the Model Layer 18:19 — Why 80–90% of Enterprise Tokens Could Be Open 20:57 — The Future Is Local and Cloud 26:40 — Why AI Is Coming Back to Your Computer 28:56 — The Coming Era of Unlimited Tokens 32:30 — Do We Still Need a “God Model”? 33:41 — Open Models and Geopolitics 36:14 — The Origins of Ollama 40:36 — Two Years Lost in the Wilderness 42:39 — The Pivot That Changed Everything 47:02 — How Ollama Found a Business Model 49:43 — Why Second-Time Founders Did YC
Y Combinator313,654 Aufrufe • vor 1 Monat
Stage is a code review platform designed to help engineers understand AI-generated code. Your team is drowning in an endless backlog of PRs. Stage turns code review into a guided process and enables you to review changes faster than using GitHub. Congrats on the launch, Charles Pan and Dean Stratakos!
Y Combinator1,063,952 Aufrufe • vor 5 Monaten