Y Combinator Startup Podcast

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

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

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.

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.

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.