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StartupFactory

Y Combinator, tech’s unicorn builder extraordinaire

YC Sunday cover

The world’s most important accelerator is deep into AI

P (YC) = 1

Many things get described as “a certainty” or “a guarantee” when in fact the difference between 90% likely, 99% likely, and 99.9% likely — which is significant — is often ignored.

With that disclaimer in mind, I am as close to 100% certain as it is possible to be that if you have been even a moderate internet user for more than a few years, you’ve come into contact with, either directly or indirectly, a portfolio company of the world’s pre-eminent startup accelerator: Y Combinator (YC).

Indeed, if you’ve ever bought anything on the internet that uses Stripe, ordered food on an app (DoorDash), scrolled Reddit, watched video games on Twitch, visited any of the 400,000+ websites hosted on Webflow, stayed in an Airbnb, ordered groceries on Instacart, bought crypto on Coinbase, shared a file on Dropbox, or interacted with any of the 2.2 million businesses that use Zapier’s software to automate their processes, then you’ve come into contact with a YC company. And, if by some utter miracle you haven’t done any of those things, there’s another ~5,000 companies backed by YC that you could have crossed paths with.

So how did YC, which started with just $200k in capital from its founders who “wanted to learn how to be angel investors”, become the most influential early-stage investing firm in the world?

Like similar accelerators, the core YC program involves a bootcamp of sorts. For 3 months founders live and breathe all things “startup”, working hard to make as much progress on their companies before Demo Day — when the latest crop of would-be-world-changers pitch to investors and media.

Startup factory

The secret of YC’s unique success is debated. But a combination of good judgment, a focus on technical founders making something people want (YC’s mantra), a culture of mentorship and collaboration, standardized investing terms, and a good old-fashioned dose of “right time and right place” can certainly lay some claim to the $600B+ value that’s now attributed to YC-backed startups.

The founders selected tend to be at a very early stage — the winter 2023 batch included 52% of applicants with only an idea and 77% of the batch had zero revenue before starting the program. Investing in those sorts of companies is inherently about as risky as it gets… which is why the firm never puts all of its eggs in one basket.

After backing just 8 companies in its first batch...
YC cohorts started getting bigger...
and the hit investments started stacking up.
From 2017 to 2019, nearly 900 startups went through YC
Since 2020, more than 2500+ startups have done YC

By investing in hundreds of companies every year, YC maximizes its odds of beating the golden law that governs much of early-stage investing: most investments will fail, but even a small number of hits can make it all worth it — and YC has certainly had its share of hits. Indeed, as YC companies went on to have success, the company’s twice-yearly programs, one in the summer and one in the winter, fell into a virtuous circle. Once YC alumni had success, hungry founders started applying in their thousands… YC got to pick the best ones for its program, investors wanted to back YC graduates… those companies were more likely to be successful… and so on and so forth.

Make something people want

Indeed, YC’s reputation now precedes it, enabling its partners to be incredibly selective: its most recent batch took in less than 1% of applicants. What those applicants are working on is a good signal for what the prevailing wisdom of Silicon Valley believes will define our future.

The conclusion from looking at the data? It’s all about AI. Indeed, per our calculations, a staggering 64% of the 2024 winter batch of YC had "AI" or “AI-related” tags in their Y Combinator company profile in the company’s startup directory.

YC’s cohorts are now dominated by startups working on AI

YC’s own definition of AI-focused was more diluted, citing “at least 50%” of the most recent batch building around it in one form or another. It’s also likely that some of those startups aren’t really doing anything groundbreaking in AI, but just incorporating some AI into their product strategically — which would be hard to blame them for considering that investors are blindly throwing money at anything that looks like AI. Whichever way you slice it, AI is the common thread.

So, what are those founders working on? 

Well, there’s a startup that wants to build an “AI creative suite for the fashion industry”, one working on “AI-powered PowerPoint”, one doing “Professional Quality AI Music”, one building “AI for Robot Arms in Factories” and one whose product offer is “Type a script, get a movie” (paging Hollywood’s unions?).

Interestingly, you can track tech hype cycles throughout YC cohorts. In 2022, when “Crypto / Web 3” was the hottest thing to work on, 33 YC startups were working in the space — in the most recent batch there was only 1.

The Bookface effect

Like so many walks of life, success in tech is rarely only about what you know, but who you know. Getting that first customer, being introduced to a potential key hire, finding that friend of a friend who can point you in the right technical direction… Y Combinator’s true superpower is now in its network. At the center of its community is Bookface: YC’s internal social network, which in the words of Garry Tan, YC’s CEO & President, was needed because “because YC had funded larger batches and the hardest part of a community is knowing who is in it and who you can trust and ask for help”. 

That community is increasingly influential and vast. YC’s original 4 founders, Paul Graham, Jessica Livingstone, Robert Morris, and Trevor Blackwell have all since moved on. But, the company’s leadership has been a who’s who of tech power players even when they weren't leading it: most notable being Sam Altman, who led YC before becoming the fired-then-rehired CEO of OpenAI.

Who wants to be an entrepreneur?

It would be overly charitable to give YC or its peers (of which there are many) sole credit for the tech startup ecosystem that flourished in the last 20 years, but it certainly played a part. Its rise has coincided with 20-something billionaires fronting magazine covers, technology companies becoming the driving force in the American economy and tech investing entering the mainstream in TV, movies and books. Put simply, America seems to revere entrepreneurs more than ever and the venture capital industry has boomed as a result (per data from the NVCA).

VC AUM has boomed

Going SAFE

Apart from its direct output, arguably YC’s most important contribution was the standardized investing documents that it introduced which made investing in two-people-who-have-a-cool-idea a little less legally onerous.

Initially, YC offered a straightforward $20K in exchange for around a 6% equity stake. Today, YC’s pockets are (a lot) deeper, and the proposition is $500K split into two parts — a $125K Simple Agreement for Future Equity (SAFE) for 7% equity and a further $375K that converts at terms realized in the future. The “SAFE” is a YC invention from 2013 that allows investors to cut a check now, which converts into equity at a later milestone. Standardizing the offer and the legal docs skips the messy part — negotiating a price and valuation — with each individual company and has since been adopted by a number of other early-stage investors.

Now, nearly two decades on from its first group of hackers, YC is the force in early-stage investing, particularly in San Francisco. At the end of March, Forbes reported that the company was raising $2 billion for its bi-annual accelerator and follow-on investments. That’s 10,000x the capital that the founders first put in.

Y Combinator is a neon orange big tent tech church, welcoming anyone under its roof who wants to worship at the altar of two things: (1) Building technology that changes the world, (2) Making a lot of money. It’s gotten pretty good at both.

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WSJ: Anduril’s weapons systems have failed during several tests

Autonomous drones by sea, land, and air. Futuristic AI-powered support fighter jets, and swarms of networked drones controlled by sophisticated software. These are some of the visions for the future of warfare pitched by defense tech startup Anduril. Cofounded by Oculus founder Palmer Luckey, the Peter Thiel-backed startup has landed some major national security contracts based on this futuristic outlook for battlefield AI.

But according to a report from The Wall Street Journal, the company’s tech is failing key tests in the real world, raising concerns about the viability and safety of Anduril’s systems within the military command.

Anduril’s Altius drones proved vulnerable to Russian jamming while deployed in Ukraine and have been pulled from the battlefield, per the report.

More than a dozen sea-based drone ships powered by Anduril’s Lattice command and control software recently shut down during a Navy test, creating a hazard for other vessels in the exercise.

And this summer, during a drone intercept test, Anduril’s counter-drone system crashed and caused a 22-acre fire at a California airport, the report found.

Anduril told the WSJ that the failures are just part of its rapid iterative development process:

“We recognize that our highly iterative model of technology development — moving fast, testing constantly, failing often, refining our work, and doing it all over again — can make the job of our critics easier. That is a risk we accept. We do fail… a lot.”

But according to a report from The Wall Street Journal, the company’s tech is failing key tests in the real world, raising concerns about the viability and safety of Anduril’s systems within the military command.

Anduril’s Altius drones proved vulnerable to Russian jamming while deployed in Ukraine and have been pulled from the battlefield, per the report.

More than a dozen sea-based drone ships powered by Anduril’s Lattice command and control software recently shut down during a Navy test, creating a hazard for other vessels in the exercise.

And this summer, during a drone intercept test, Anduril’s counter-drone system crashed and caused a 22-acre fire at a California airport, the report found.

Anduril told the WSJ that the failures are just part of its rapid iterative development process:

“We recognize that our highly iterative model of technology development — moving fast, testing constantly, failing often, refining our work, and doing it all over again — can make the job of our critics easier. That is a risk we accept. We do fail… a lot.”

tech

OpenAI’s partners shouldering $100 billion of debt, taking on all the risk

OpenAI’s ambitious plans for global AI infrastructure projects — like its series of massive Stargate AI data centers — will require tens of billions of dollars funded by debt, but you won’t find much of that on OpenAI’s balance sheet.

According to a new analysis by the Financial Times, OpenAI has somehow convinced its many partners to shoulder at least $100 billion in debt on its behalf, as well as the risks that come with it.

Partners Oracle, SoftBank, CoreWeave, Crusoe, and Blue Owl Capital are all taking on debt in the form of bonds, loans, and credit deals to meet their obligations with OpenAI for infrastructure and computing resources.

Having close ties with OpenAI has been an anchor for many publicly traded companies in recent weeks. The company’s cash burn and the rise of Gemini 3 have seemingly darkened its outlook and fostered guilt by association for many of its close partners and investors. Most notably, Oracle’s aggressive capital expenditure plans to support demand from OpenAI have sparked a sell-off in its stock while widening its credit default swap spreads.

A senior OpenAI executive told the FT: “That’s been kind of the strategy. How does [OpenAI] leverage other people’s balance sheets?”

Partners Oracle, SoftBank, CoreWeave, Crusoe, and Blue Owl Capital are all taking on debt in the form of bonds, loans, and credit deals to meet their obligations with OpenAI for infrastructure and computing resources.

Having close ties with OpenAI has been an anchor for many publicly traded companies in recent weeks. The company’s cash burn and the rise of Gemini 3 have seemingly darkened its outlook and fostered guilt by association for many of its close partners and investors. Most notably, Oracle’s aggressive capital expenditure plans to support demand from OpenAI have sparked a sell-off in its stock while widening its credit default swap spreads.

A senior OpenAI executive told the FT: “That’s been kind of the strategy. How does [OpenAI] leverage other people’s balance sheets?”

tech

Chinese tech giants are training their models offshore to sidestep US curbs on Nvidia’s chips

Nvidia can’t sell its best AI chips in the world’s second-largest economy. That’s an Nvidia problem. But it’s also a China problem — and it’s one that the region’s tech giants have resorted to solving by training their AI models overseas, according to a new report from the Financial Times.

Citing two people with direct knowledge of the matter, the FT reported that “Alibaba and ByteDance are among the tech groups training their latest large language models in data centers across south-east Asia.” Clusters of data centers have particularly boomed in Singapore and Malaysia, with many of the sites kitted out with Nvidia’s latest architecture.

One exception, per the FT, is DeepSeek, which continues to be trained domestically, having reportedly built up a stockpile of Nvidia chips before the US export ban came into effect.

Last week, Nvidia spiked on the news that the Trump administration was reportedly considering letting the tech giant sell its best Hopper chips — the generation of chips that preceded Blackwell — to China.

Citing two people with direct knowledge of the matter, the FT reported that “Alibaba and ByteDance are among the tech groups training their latest large language models in data centers across south-east Asia.” Clusters of data centers have particularly boomed in Singapore and Malaysia, with many of the sites kitted out with Nvidia’s latest architecture.

One exception, per the FT, is DeepSeek, which continues to be trained domestically, having reportedly built up a stockpile of Nvidia chips before the US export ban came into effect.

Last week, Nvidia spiked on the news that the Trump administration was reportedly considering letting the tech giant sell its best Hopper chips — the generation of chips that preceded Blackwell — to China.

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Millie Giles

Alibaba unveils its first AI glasses, taking on Meta directly in the wearables race

Retail and tech giant Alibaba launched its first consumer-ready, AI-powered smart glasses on Thursday, marking its entrance into the growing wearables market.

Announced back in July, the Quark AI glasses just went on sale in the Chinese retailer’s home market, with two versions currently available: the S1, starting at 3,799 Chinese yuan (~$536), and the G1, at 1,899 yuan (~$268) — a considerably lower price than Meta’s $799 Ray-Ban Display glasses, released in September.

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Jon Keegan

Musk: Tesla’s Austin Robotaxi fleet to “roughly double” next month, but falls well short of earlier goals

Yesterday, Elon Musk jumped onto a frustrated user’s post on X, who was complaining that they were unable to book a Robotaxi ride in Austin. Musk aimed to reassure the would-be customer that the company was expanding service in the city:

“The Tesla Robotaxi fleet in Austin should roughly double next month,” Musk wrote.

While that sounds impressive, there are reports that Austin has only 29 vehicles in service.

But last month, Musk said the Robotaxi goal was to have “probably 500 or more in the greater Austin area” by the end of the year.

Meanwhile, Google’s Waymo has more than 100 autonomous taxis running in Austin, and 1,000 more in the San Francisco Bay Area.

“The Tesla Robotaxi fleet in Austin should roughly double next month,” Musk wrote.

While that sounds impressive, there are reports that Austin has only 29 vehicles in service.

But last month, Musk said the Robotaxi goal was to have “probably 500 or more in the greater Austin area” by the end of the year.

Meanwhile, Google’s Waymo has more than 100 autonomous taxis running in Austin, and 1,000 more in the San Francisco Bay Area.

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