Y Combinator
Advice, stories, and research from Y Combinator: practical guidance for founders, deep dives on AI and biotech trends, and conversations with founders who scaled high-growth startups.
Past bets that played out
Highlights include: a YC/Light Cone interview framing robotics as nearing a "GPT-1 moment" for general-purpose robot control models; Demis Hassabis on missing ingredients for AGI and the path toward agentic systems; and a company profile on BillionToOne describing progress in blood-based prenatal DNA screening and plans for an MRD oncology test.
YC/Light Cone interview with Physical Intelligence co-founder Kwan Vuong frames robotics as approaching a “GPT-1 moment”: a general-purpose AI control model that can operate many robot embodiments across many tasks. The key market-relevant points are: robotics autonomy may emerge incrementally rather than suddenly; mixed-autonomy systems can be commercially useful before full autonomy; deployment in real-world jobs creates a data flywheel from edge cases; and a foundation-model/platform layer could become a differentiator.
Demis Hassabis argues that current AI systems still lack key ingredients for AGI—continual learning, long-term reasoning, memory, and active agentic problem-solving—but believes AGI could arrive around 2030. The discussion frames agents as the likely path from today’s large-scale pretraining/RLHF/chain-of-thought paradigm toward more general intelligence. It highlights Google DeepMind’s track record, including AlphaGo, AlphaFold, and Gemini, positioning Alphabet as one of the leading companies.
Promotional/company-profile source on private BillionToOne, a molecular diagnostics company using blood-based DNA detection for prenatal genetic testing and oncology. The key market-intelligence points are that its prenatal test has reached meaningful U.S. penetration, cited as screening roughly 1 in 11 babies, and that the company says it is less than a year from launching an ultra-sensitive minimal residual disease (MRD) test for stage 1/2 cancer patients.
What this channel is watching now
Frequent coverage and discussion center on major technology companies and AI platform providers. Top tickers by mentions and conviction: NVDA (highest mentions), MSFT, GOOGL, AMZN, plus notable attention to AI labs such as ANTHROPIC and OPENAI. Themes emphasize AI research directions, agentic systems, and commercialization pathways for robotics and biological applications of machine learning.
Latest videos and market context
Recent videos include actionable founder advice from Startup School (How To Pick A Startup Idea), thematic research recaps (YC Paper Club: where AI research is heading), a founder fireside on Meesho’s growth in India, and short-form commentary on product-market fit (Groww title with limited content).
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 General Partner 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. Apply to Y Combinator: https://www.ycombinator.com/apply Work at a startup: https://www.ycombinator.com/jobs Chapters: 00:00 — Intro 00:59 — The "Perfect Idea" trap 02:42 — Why working on multiple ideas fails 03:21 — How to actually go deep 04:51 — Could you run your customer's business? 06:18 — Build at the edge of what AI can do 08:37 — Aim at the most ambitious version 09:33 — What happens when the idea fails 10:27 — Walk fast in one direction
Groww: If Your Customers Don't Love It or Hate It, You've Already Lost
The provided source only contains a title repeated in the body with no additional context, claims, companies, products, metrics, or market linkages. It is not actionable for investment analysis as-is.
5 Papers That Show Where AI Research Is Heading Right Now
YC Paper Club recap highlighting emerging AI research directions: scaling laws applied to protein biology (ESM), AlphaZero-style self-play for LLMs, streaming RAG for real-time voice agents, formal verification with Lean, and “agentic” programming workflows. This is directional/strategic (themes) rather than a specific catalyst with near-term dates.
How Meesho Became India’s Biggest Shopping App
Fireside chat describes Meesho’s rapid scale in India mass-market e-commerce/social commerce (Android #1 shopping app; ~1M sellers; claimed very high order volume), key pivots (WhatsApp-group distribution; business-model changes after Jio disrupted earlier assumptions), and forward-looking theme around voice/AI to expand addressable buyers. Meesho is private; implications are second-order for listed India e-commerce competitors, logistics, payments, telco, and digital ads/cloud.
Proof-backed call history
Y Combinator invests in startups, provides intensive three-month programs, and supports founders for the life of their companies with community, advice, funding access, recruiting resources, and exclusive deals. YC posts recorded talks, panels, and research recaps that document founder experiences and evolving technology themes.
Discussion of rapid progress in open-model research where teams are addressing longstanding unsolved problems; mentions recent claimed breakthroughs from OpenAI and work from DeepMind cited in promotional material.
Research on interpretability: efforts to understand what models learn by applying sparse-coding–style analyses to model activations in search of human-interpretable features, similar to work in language-model interpretability.
YC Paper Club recap highlighting emerging AI research directions: scaling laws applied to protein biology (ESM), AlphaZero-style self-play for LLMs, streaming RAG for real-time voice agents, formal verification with Lean, and “agentic” programming workflows. This is directional/strategic (themes) rather than a specific catalyst with near-term dates.
YC Paper Club recap highlighting emerging AI research directions: scaling laws applied to protein biology (ESM), AlphaZero-style self-play for LLMs, streaming RAG for real-time voice agents, formal verification with Lean, and “agentic” programming workflows. This is directional/strategic (themes) rather than a specific catalyst with near-term dates.
YC Paper Club recap highlighting emerging AI research directions: scaling laws applied to protein biology (ESM), AlphaZero-style self-play for LLMs, streaming RAG for real-time voice agents, formal verification with Lean, and “agentic” programming workflows. This is directional/strategic (themes) rather than a specific catalyst with near-term dates.
YC Paper Club recap highlighting emerging AI research directions: scaling laws applied to protein biology (ESM), AlphaZero-style self-play for LLMs, streaming RAG for real-time voice agents, formal verification with Lean, and “agentic” programming workflows. This is directional/strategic (themes) rather than a specific catalyst with near-term dates.
YC Paper Club recap highlighting emerging AI research directions: scaling laws applied to protein biology (ESM), AlphaZero-style self-play for LLMs, streaming RAG for real-time voice agents, formal verification with Lean, and “agentic” programming workflows. This is directional/strategic (themes) rather than a specific catalyst with near-term dates.
YC Paper Club recap highlighting emerging AI research directions: scaling laws applied to protein biology (ESM), AlphaZero-style self-play for LLMs, streaming RAG for real-time voice agents, formal verification with Lean, and “agentic” programming workflows. This is directional/strategic (themes) rather than a specific catalyst with near-term dates.
YC Paper Club recap highlighting emerging AI research directions: scaling laws applied to protein biology (ESM), AlphaZero-style self-play for LLMs, streaming RAG for real-time voice agents, formal verification with Lean, and “agentic” programming workflows. This is directional/strategic (themes) rather than a specific catalyst with near-term dates.
Fireside chat describes Meesho’s rapid scale in India mass-market e-commerce/social commerce (Android #1 shopping app; ~1M sellers; claimed very high order volume), key pivots (WhatsApp-group distribution; business-model changes after Jio disrupted earlier assumptions), and forward-looking theme around voice/AI to expand addressable buyers. Meesho is private; implications are second-order for listed India e-commerce competitors, logistics, payments, telco, and digital ads/cloud.
Fireside chat describes Meesho’s rapid scale in India mass-market e-commerce/social commerce (Android #1 shopping app; ~1M sellers; claimed very high order volume), key pivots (WhatsApp-group distribution; business-model changes after Jio disrupted earlier assumptions), and forward-looking theme around voice/AI to expand addressable buyers. Meesho is private; implications are second-order for listed India e-commerce competitors, logistics, payments, telco, and digital ads/cloud.
Fireside chat describes Meesho’s rapid scale in India mass-market e-commerce/social commerce (Android #1 shopping app; ~1M sellers; claimed very high order volume), key pivots (WhatsApp-group distribution; business-model changes after Jio disrupted earlier assumptions), and forward-looking theme around voice/AI to expand addressable buyers. Meesho is private; implications are second-order for listed India e-commerce competitors, logistics, payments, telco, and digital ads/cloud.
About this channel
Y Combinator is an accelerator and investor that invests $500,000 in every startup it accepts and works closely with founders during its program. Content on the channel focuses on startup playbooks, founder stories, and technology research that informs product and company strategy.
All the world is changing around technology and you may contribute a line of code. What will yours be? Subscribe for startup advice, founder stories, and a look inside Y Combinator. What is Y Combinator? We invest $500,000 in every startup and work intensively with the founders for three months. For the life of their company, founders have access to the most powerful community in the world, essential advice, later-stage funding and programs, recruiting resources, and exclusive deals. Visit ycombinator.com to learn more.
Most recognized assets
Unlock the full track record
Apply to Y Combinator at https://www.ycombinator.com/apply, find jobs at startups through https://www.ycombinator.com/jobs, and visit ycombinator.com to learn more.
65 more thesis calls are available after sign-up.