Danny Chepenko
We've been covering YC batches as a quarterly snapshot of what technology makes possible. But something materially changed in W26.
Some headlines from the batch:
- Roughly 1 in 5 W26 companies isn't building traditional software
- 3X more companies in this batch reached $1M annualized revenue than W25
- 22 solo founders in the batch — 11% of W26 is one person building alone
- One company closed a Fortune 100 deal in 3 weeks
- A 22-year-old dropout is building the first hotel on the Moon and presented his Moon brick to the US Congress
- 3 companies had raised substantial funding prior to YC: Ndea ($43M), Mango Medical ($8.3M), Beacon Health ($5.4M)
We compiled a detailed dataset mapping traction across the entire W26 batch, 199 companies with 14 data columns covering funding, KPIs, founder backgrounds, prior employers, education, and business model classification. It saves investors and founders dozens of hours of research.
YC Is Becoming More YC
There's a common criticism of YC under Garry Tan: it's not like the good old days, the partners are doing weird stuff, the batch is a B2B zoo. Nostalgia is neat. But steering one of the most important innovation institutions in the world through an AI revolution is not a trivial task.
Yeah, I mean that common criticism
Here's what the data actually says: YC under new leadership is returning to its historical roots. The batch is attracting younger, more technical, more pedigreed founders, working on crazier, harder-to-replicate ideas.
The average founder in W26 has 5.8 years of professional experience, down from the historical YC average of ~9 years between school and batch. And AI agent founders sit even lower at a 4.8-year median - they're younger, moving fast into the newest category.
Look at what YC actually funded this time:
LLM. There are 3 foundational LLM research companies: Ndea (43M AGI lab, co-founded by François Chollet, creator of Keras, one of the most widely used deep learning frameworks), Confluence Technologies (scored 97.9% on ARC-AGI-2, one of the leading benchmarks for measuring general intelligence in AI), and Rubric (post-training research at exabyte scale).
Hardware. 18 hardware companies are building physical things: Moon hotels, autonomous cattle drones, dive gear for space, warehouse robots, radars for self-driving.
Bio. 3 bio companies are doing real drug discovery, Ditto Bio is finding autoimmune therapies in parasitic proteins, Origin Bio built a DNA model that outperforms DeepMind's AlphaGenome, and CellType is simulating human biology from scratch.
And more. There's a company doing AI-powered uranium exploration (Terranox AI). Another one built the fastest inference engine on Apple Silicon, beating Apple's own MLX (RunAnywhere, 10.2K GitHub stars). Byteport built a file transfer protocol that is 10x faster than TCP. On unreliable connections like cellular or satellite, they're showing 1000x speedups.
That shift tells you everything about where YC thinks the puck is going - SaaSpocalypse is real. The batch is tilting hard toward deep-tech, things that are genuinely difficult to build, require real scientific expertise, and can't be replicated by a weekend hackathon with an API key.
Let's dive deeper.
What They're Building: 199 Companies, 8 Categories
We classified every company in the batch using Extruct's enrichment:
AI agents (37), still the largest single category — but a sharp reversal from recent batches. In Spring 2025, AI agents made up ~49% of the batch (67 of 144 companies). In S25, it was ~50%. In W26 it's 19%. YC cut the agent's share by more than half. The agents that did get in are deeply verticalized: Patientdesk.ai (AI dental receptionist), Wayco (AI law firm operator), Corvera (AI supply chain manager), Robby (AI HVAC documenter), Veriad (AI compliance officer).
Devtools (29), the builder-for-builders layer. Bubble Lab (open-source agentic workflow builder), Sparkles (make everyone on your team an engineer), Sonarly (production alerts you can trust), compresr (LLM context compression, integrated with Claude Code).
AI infra/research (20), this is where W26 gets weird. Three companies orbit the same AGI benchmark: ARC Prize Foundation (runs ARC-AGI), Ndea (Chollet's $43M lab, he designed ARC-AGI), and Confluence Technologies (scored 97.9% on ARC-AGI-2, essentially saturating it at $11.77/task). The benchmark, the benchmark creator, and the solver, all in one batch. Beyond that, 8 of 20 AI infra companies are building training data and environments. The batch is betting the bottleneck is data, not models.
Hardware/physical (18):
Space (4) — GRU Space (first hotel on the Moon), General Astronautics (autonomous robots for in-space manufacturing), Kyten Technologies (custom aerospace-grade battery packs), Beyond Reach Labs (solar arrays that grow to football-field size in orbit).
Robotics & drones (5) — Servo7 (autonomous warehouse robots, AI-powered pick-and-pack), GrazeMate (autonomous AI drones that muster cattle), Origami Robotics (general-purpose manipulation), Voltair (self-charging drones inspecting power lines), RoboDock (autonomous depots for autonomous fleets).
Defence & sensing (3) — DroneTector (hostile drone detection radar), Seeing Systems (AI drone systems for defence), Congruent (radars for end-to-end vehicle autonomy).
Consumer devices & wearables (4) — Pocket (AI note-taking device, $27M ARR, 30K+ units shipped, 50% MoM — the revenue outlier of the entire batch), Fort (strength training wearable, auto-counts reps, tracks longevity metrics), Button Computer (wearable AI that can talk, 2 ex-Apple Vision Pro engineers), DAIVIN (world's first tankless dive gear, extending to space).
Fintech / payments (11), the interesting sub-cluster here is building financial rails for the agent economy: Maven (payments for voice AI agents), Sponge (wallets for agents), Orthogonal (APIs payable by agents).
Healthcare (~28 companies, the densest vertical), spans across categories but deserves its own callout. Beacon Health (AI-enhanced preventive cardiovascular care, $5.4M raised), Mango Medical (simulates orthopedic surgeries from CT scans), Eos AI (autonomous OS for healthcare), ClaimGlide (automated prior-auths), Patientdesk.ai (AI voice agent for patient calls). YC is betting hard on AI x healthcare.
Consumer apps (5) and Marketplaces (5), small but notable. Though Pax Historia (AI sandbox game, play any moment in history) pulled 2,334 likes on its YC launch tweet, the highest of any company.
Who's Building: The Founder Profile
Conventional wisdom says 2 co-founders is the optimal startup team structure. W26 confirms this, 128 companies (65%) have exactly 2 co-founders.
But the more interesting number is 22: that's how many solo founders are in the batch. 11% of W26 is one person building alone. And the domain is weird either — GRU Space (Skyler Chan, 22, building a Moon hotel), DAIVIN (Leo Kankkunen, tankless dive gear), GrazeMate (Sam Rogers, robot cowboys), Fission AI, Rhizome AI, Cumulus Labs. Fintech has zero solo founders, regulated markets apparently require a partner. Devtools has the highest solo rate at 22%.
Where they come from tells you what they're building.
Hardware startups trace back to Tesla, SpaceX, Apple, the companies where founders learned to ship atoms. Button Computer's founders built Apple Vision Pro. Fintech is an Apple-and-Google story. AI infra has 2 startups with NASA alumni, the research layer draws from unusual places. AI agent companies lean Amazon and Meta, plus consulting (McKinsey).
Overall, Amazon is the #1 feeder: 14 W26 startups have at least one ex-Amazonian. Apple is second at 12.
The university pipeline: Berkeley dominates with 30 founders, nearly 1.5x Stanford (22). Harvard is third at 18. The top 3 account for 70 founders, ~16% of the batch.
Geography: San Francisco is the center of gravity. Again. 69 companies are headquartered in SF proper. Add the broader Bay Area (Berkeley, Palo Alto, San Mateo, Sunnyvale) and California accounts for 78 out of 117 companies with location data, 67%. New York is a distant second at 9. The batch is heavily concentrated.
The non-US cohort skews toward deep domain problems, energy, defence, healthcare, and industrial robotics. Worth noting: no startups from emerging markets. Outside the core EU hubs (London, Munich, Amsterdam), the only surprises are Copenhagen and Sydney.
Top Launches by Twitter Engagement
YC launch tweets are the first public signal of which companies resonate. High engagement doesn't guarantee success, but it shows what captures attention from founders, investors, and engineers who follow. It's also a leading indicator of which companies will have an easier time with distribution post-Demo Day.
What the crowd responded to, ranked by likes on @ycombinator launch tweets:
- Pax Historia (2,334 likes) — AI sandbox game where you can play any moment in history
- Pocket (2,076) — $27M ARR, 30K+ units, 50% MoM growth
- Skillsync (1,854) — hire devs by GitHub, not resumes
- Cardboard (1,480) — agentic video editor, hit revenue goal in 4 hours
- Fort (1,295) — strength training wearable
- GrazeMate (1,210) — autonomous cattle drones
- GRU Space (1,098) — Moon hotel, 22yo solo founder
Hardware and "weird" companies dominate. 4 of the top 9 build physical things.
The Bottom Line
YC W26 is the deepest-tech batch in recent memory. The SaaSpocalypse talk is reflected in what YC actually funded. Hardware is back. Foundational AI research is in. Healthcare is defined. The founders are younger but more technical, coming from Tesla and SpaceX instead of consulting firms, building things that are genuinely hard to replicate.
Gustaf said this is the best batch he's ever seen. The data backs him up.