Y Combinator published its Summer 2026 Request for Startups in late April, just days before the application deadline. The document lists 15 categories of companies that YC’s partners want to fund. Eight of them require capital, hardware, or both. The list includes AI for low-pesticide agriculture, counter-swarm drone defence, inference chips for space, lunar manufacturing from molten regolith, and semiconductor supply chain software for a process that crosses a dozen countries and takes five months to complete.

Each category is written by a named partner, and each reads less like a startup prompt than a thesis on why the economics of a particular industry have just shifted. The most influential startup accelerator in the world, the institution that funded Airbnb, Stripe, and Dropbox, is telling founders that the next decade of billion-dollar outcomes will come not from building software but from using AI to enter the physical, regulated, and capital-intensive industries that software alone never touched.

The thesis

The RFS opens with Garry Tan, YC’s chief executive, writing about agriculture. AI can now identify individual weeds and pests in real time, he argues, and when combined with robotic precision treatments, the result is farming that uses dramatically less pesticide while improving yield. The category is not agtech in the way Silicon Valley has historically understood it, which meant software dashboards for farm management. It is agtech that involves building physical robots, training vision models on biological data, and deploying hardware in fields.

Tyler Bosmeny’s entry on counter-swarm defence compares the companies he wants to fund to Cloudflare rather than Raytheon, software-defined defence systems that neutralise drone swarms at a fraction of the cost of traditional missile systems. The United States Department of Defense proposed more than $70 billion for drone and counter-drone systems in its latest spending plan, and defence tech is experiencing its strongest investment cycle in decades. Adi Oltean asks for founders who will 3D-print structures from molten lunar regolith and extract raw materials including silicon, aluminium, iron, and titanium through electrolysis on the moon.

The hard-tech categories are not aspirational filler. They reflect a structural change in what venture capital is willing to fund. Defence tech startups raised a record $49.1 billion in 2025, nearly double the prior year. Anduril, the autonomous weapons company, raised $4 billion at a $60 billion valuation in March. SpaceX has demonstrated that hardware-intensive businesses can produce venture-scale returns. The old assumption that hardware could not generate the margins or the speed that venture capital requires has collapsed, and YC’s RFS is the clearest institutional acknowledgement that the collapse is permanent.

The software that remains

Seven of the 15 categories are software, but none of them resemble the SaaS playbook that defined the previous decade. The category YC calls Software for Agents asks founders to rebuild every major software category for a world where the next trillion users are not people but AI agents. That means APIs, machine-readable documentation, command-line interfaces, identity systems, permissions layers, and payment infrastructure designed for autonomous programmes rather than human beings. Google rebranded its entire AI platform around agents at Cloud Next 2026, consolidating Vertex AI into the Gemini Enterprise Agent Platform and launching a $750 million fund to finance agentic deployments. Gartner predicts that 40 per cent of enterprise applications will include task-specific AI agents by the end of this year, up from less than 5 per cent in 2025.

The Company Brain category asks for a system that pulls knowledge out of every fragmented source inside a company, structures it, keeps it current, and turns it into what YC calls an executable skills file for AI. This is not enterprise search. It is a living map of how a company works: how refunds are processed, how pricing exceptions are decided, how engineers respond to incidents. The Dynamic Software Interfaces category is its mirror image, asking founders to rebuild software so that agents can operate it natively rather than scraping interfaces built for humans.

The SaaS Challengers category names the targets explicitly: ERP, chip design software, industrial control systems, and supply chain management. These are the categories where incumbent vendors charge the most and innovate the least, and where AI-native replacements could capture enormous markets if they can clear the switching costs.

The physical turn

The RFS entry on semiconductor supply chains may be the most revealing. A single advanced AI chip goes through approximately 1,400 process steps, crosses a dozen countries, and takes five months to manufacture. That supply chain is managed, as the RFS puts it, with spreadsheets, SAP, and phone calls. Diana Hu, the YC partner who wrote the entry, is asking for founders who will replace that infrastructure with software that can track, optimise, and predict across the most complex manufacturing process on earth.

The category sits at the intersection of every force currently reshaping the technology industry: the US-China chip export controls, the reshoring of semiconductor fabrication, the explosion in AI chip demand, and the geopolitical fragility of supply lines that route critical components through Taiwan, South Korea, the Netherlands, and Japan.

The space categories are similarly grounded in economics rather than aspiration. Reusable rockets from SpaceX and Stoke Space are about to produce a massive increase in the capacity to put objects in orbit, which means an equally massive increase in demand for the electronics that operate there.

YC wants inference chips optimised for mass, thermal performance, and radiation hardness. SpaceX and Blue Origin are already racing to put data centres in orbit, and the AI hardware that runs inference workloads in terrestrial data centres does not survive the thermal and radiation environment of space. The market for space-rated inference silicon does not exist yet. YC is betting that it will.

What changed

Y Combinator’s Spring 2026 RFS, published just three months earlier, listed eight categories. The Summer edition nearly doubled that to 15. The Spring list included AI for product management, government AI, AI-native hedge funds, and stablecoins. Those are recognisably software businesses with AI bolted on. The Summer list includes lunar regolith manufacturing and counter-drone defence systems. The shift between the two documents is the most dramatic reorientation in YC’s public investment thesis since the accelerator began publishing requests for startups.

The change reflects what has happened to venture capital more broadly. In the first quarter of 2026, $297 billion flowed into startups globally, 2.5 times the prior quarter and the most venture funding ever recorded in a three-month period. Accel raised a $5 billion fund on the back of returns from Anthropic and Cursor.

Andreessen Horowitz raised $15 billion. Thrive Capital closed more than $10 billion. The money is not looking for the next enterprise SaaS dashboard. It is looking for the companies that will apply AI to the industries where the margins are highest, the incumbents are slowest, and the barriers to entry have historically been physical rather than digital. YC’s RFS is the most explicit version of that thesis because it names the industries by name: agriculture, defence, space, semiconductors, medicine, manufacturing.

The stablecoin category, one of the few holdovers from the Spring list, reveals a different kind of ambition. YC describes stablecoins as sitting between the regulated and unregulated worlds, creating room for services that combine the strengths of both: yield-bearing accounts, tokenised real-world assets, and infrastructure that moves money faster and cheaper across borders. The AI Personalised Medicine category asks for agents that analyse genomic data, electronic health records, and wearable output to generate patient-specific treatment protocols rather than population-level guidelines. Neither category requires building physical hardware. Both require operating in industries where regulation, liability, and institutional trust are the barriers, not code.

The signal

YC’s Request for Startups is not a prediction. It is a commitment. The partners who write the entries are the partners who will evaluate the applications, and the categories they describe are the companies they will fund. When Garry Tan writes about agriculture robots and Tyler Bosmeny writes about counter-drone systems and Adi Oltean writes about 3D-printing on the moon, they are telling founders what the next YC batch will look like. The document is the closest thing the startup ecosystem produces to a forward-looking investment mandate from its most influential institution.

The mandate says that software is now the substrate, not the moat. The models are commoditising. The infrastructure is scaling. The interfaces are being rebuilt for agents. What remains scarce is the ability to apply that substrate to the physical world: to build the robot that replaces the pesticide, the chip that survives the radiation, the defence system that costs less than the drone it destroys, the supply chain software that tracks 1,400 process steps across 12 countries, the molecular model that designs a drug for a target the industry called undruggable.

Y Combinator built its reputation by funding two founders in a garage writing code. Its Summer 2026 RFS is a document that says the garage is no longer enough. The founders it wants now are the ones who can write the code and then build the thing.