Overview
YC's RFS document represents their current view of where the biggest opportunities lie. Several ideas come directly from YC founders seeing opportunities on the frontier.
Key RFS Areas
Cursor for Product Management
"Writing code is only part of building a product. The most important part is figuring out what to build." YC wants a tool where you upload customer interviews and usage data, ask "what should we build next?", and get feature outlines backed by customer feedback with development tasks broken down for coding agents. See AI-Native Product Development.
AI-Native Agencies
"Instead of selling software to customers to help them do the work, you can charge way more by using the software yourself and selling the finished product at 100x the price." Design firms, ad agencies, law firms — AI agencies will have software margins and scale far bigger than traditional agencies.
AI-Native Hedge Funds
"The next Renaissance, Bridgewater, and D.E. Shaw's are going to be built on AI." Current large funds are slow to adapt — one founder couldn't even get compliance approval to use ChatGPT. The alpha is in entirely new strategies, not bolting AI onto existing ones.
Government AI Tools
Two angles: (1) Government needs AI to process the huge increase in AI-assisted form submissions. (2) Fraud investigation — the False Claims Act's qui tam provision lets private citizens file lawsuits on behalf of government. AI can dramatically speed up evidence organization for whistleblower law firms. "Medicare alone loses tens of billions a year to improper payments."
Reindustrialized American Mills
American metal mills have 8-30 week lead times because their systems were designed decades ago. AI-driven planning, real-time MES, and modern automation can compress lead times and raise margins. The opportunity: "software-defined American mills" especially in aluminum rolling and steel tube.
AI-Guided Physical Work
"The Matrix's 'I know Kung Fu' moment for physical work." Real-time AI guidance through small cameras and earbuds for field services, manufacturing, healthcare. Three convergences: multimodal models can now reason about real-world situations, hardware is everywhere (phones, AirPods, smart glasses), and skilled labor shortages make it economically urgent.
Spatial Reasoning Models
"Unlocking the next wave of AI capability will require models that are capable of spatial reasoning." A company that succeeds could define the next AI foundation model on the scale of OpenAI or Anthropic.
Stablecoin Financial Services
The GENIUS and CLARITY Acts are placing stablecoins between DeFi and TradFi. Room for yield-bearing accounts, tokenized real-world assets, and infrastructure under traditional compliance frameworks.
LLM Training Tooling
"Training large language models is still surprisingly difficult." Broken SDKs, busted GPU instances, major bugs in open-source tooling. Need: training APIs, large dataset databases, ML-native dev environments.
The PG Foundation: "Live in the Future"
Paul Graham's classic essay "How to Get Startup Ideas" (2012) remains the philosophical foundation underlying YC's thesis. Key principles that map directly to the AI moment:
- "Live in the future, then build what's missing." People at the leading edge of AI are living in the future right now — they see gaps others can't.
- The well, not the crater. Good startup ideas start narrow and deep (small number of people who want it desperately), not broad and shallow. This explains why vertical AI (Harvey for law, coding agents for developers) beats horizontal "AI for everything."
- Schlep blindness. The best ideas involve schleps (hard, messy work) that scare away competitors. Processing payments (Stripe), processing legal documents (Harvey), automating manufacturing scheduling — the schlep is the moat.
- Organic > manufactured. The best ideas come from founders solving their own problems, not brainstorming "startup ideas." Career-Ops (evaluating 740+ job offers to land a role) is a textbook example.