Silicon Valley’s earliest stage companies are getting a major boost from artificial intelligence.
Startup accelerator Y Combinator — known for backing Airbnb, Dropbox and Stripe — this week held its annual demo day in San Francisco, where founders pitched their startups to an auditorium of potential venture capital investors.
Y Combinator CEO Garry Tan told CNBC that this group is growing significantly faster than past cohorts and with actual revenue. For the last nine months, the entire batch of YC companies in aggregate grew 10% per week, he said.
“It’s not just the number one or two companies — the whole batch is growing 10% week on week,” said Tan, who is also a Y Combinator alum. “That’s never happened before in early-stage venture.”
That growth spurt is thanks to leaps in artificial intelligence, Tan said.
App developers can now offload or automate more repetitive tasks, and they can generate new code using large language models. Tan called it “vibe coding,” a term for letting models take the wheel and generate software. In some cases, AI can code entire apps.
The ability for AI to subsidize an otherwise heavy workload has allowed these companies to build with fewer people. For about a quarter of the current YC startups, 95% of their code was written by AI, Tan said.
“That sounds a little scary, but on the other hand, what that means for founders is that you don’t need a team of 50 or 100 engineers,” said Tan, adding that companies are reaching as much as $10 million in revenue with teams of less than 10 people. “You don’t have to raise as much. The capital goes much longer.”
The growth-at-all-costs mindset of Silicon Valley during the zero-interest-rate era has gone “out the window,” said Tan, pointing to a renewed focus on profitability. That focus on the bottom line also applies to megacap tech companies. Google, Meta and Amazon have gone through multiple rounds of layoffs and pulled back on hiring.
While that’s shaken some engineers, Tan described it as an opportunity.
It’s easier to build a startup, and the top people in tech don’t have to prove their worth by going to work at big tech companies, he said.
“There’s a lot of anxiety in the job market, especially from young software engineers,” Tan said. “Maybe it’s that engineer who couldn’t get a job at Meta or Google who actually can build a standalone business making $10 million or $100 million a year with ten people — that’s such a powerful moment in software.”
About 80% of the YC companies that presented this week were AI focused, with a handful of robotics and semiconductor startups. This group of companies has been able to prove earlier commercial use compared to previous generations, Tan said.
“There’s a ton of hype, but what’s unique about this moment is that people are actually getting commercial validation,” he said. “If you’re an investor at demo day, you’ll be able to call a real customer, and that person will say, ‘Yeah, we use the software every single day.'”
Y Combinator was founded in 2005 by Paul Graham, Jessica Livingston, Robert Morris and Trevor Blackwell. The firm invests $500,000 in startups in exchange for an equity stake. Those founders then enter a three-month program at the San Francisco headquarters and get guidance from partners and YC alumni. Demo day is a way to attract additional capital.
The firm has funded more than 5,3000 companies, which it says are worth more than $800 billion in total. Over a dozen of them are public, and more than 100 are valued at $1 billion or more. More than 15,000 companies apply to get into the accelerator, with about a 1% acceptance rate.
More of these venture capital incubators have popped up throughout the past decade, and more capital has flocked to early stage startups. Despite the competition, Tan argued that Y Combinator has an edge thanks to its strong network. He pointed to the number of highly valued portfolio companies rising, and pushed back on the idea that specialized incubators were taking business.
“About 20 to 30% of the companies during YC change their idea and sometimes their industry entirely. And if you end up with an incubator that is very specialized, you might not be able to change into the thing that you were supposed to,” Tan said. “We think that the network effects and the advantages of doing YC have only become more bold.”
