Boosted by powerful new artificial-intelligence tools, Silicon Valley startups are running leaner than ever, spawning new benchmarks like revenue-per-employee and even talk of the billion-dollar, one-person company.
AI coding products like Anthropic’s Claude Code and OpenAI’s Codex, along with AI tools for sales, marketing and other functions, have reduced the need to hire, some founders and Silicon Valley insiders say.
“AI itself is just a very big enabler,” said Burkay Gur, co-founder and chief executive of AI startup Fal. “We are definitely in the camp where we take people who are extremely productive, and they become insanely productive with AI,” he said.
It might only be the beginning. The rise of independent AI agents means a single human entrepreneur could be aided by thousands, or millions of such bots, said Steve Jang, founder and managing partner of Kindred Ventures.
But some entrepreneurs say there is such a thing as being too lean, especially when selling to corporate clients who demand a human touch. Startups are trying to find the right balance.
The lean trend is particularly apparent for early-stage startups, where some founders are chasing the dream of the so-called billion-dollar, single-person startup. Median head count at Series A startups fell from about 57 employees in 2020 to about 44 in 2024, with companies becoming “increasingly lean and AI boosting productivity per employee,” said PitchBook senior AI analyst Dimitri Zabelin.
“There’ll be this huge movement of software engineers and product managers who will build very, very small head count businesses that drive $5 million to $15 million [in annual recurring revenue] and be thrilled with it, because of AI,” said Tomasz Tunguz, founder and general partner at Theory Ventures.
Henry Shi, co-founder of Super.com—itself a lean AI startup—and a member of Anthropic’s technical staff, said he began spotting posts on X last year touting the eye-popping revenues of tiny AI startups like Mercor and Cursor.
Shi realized there must be others like them out there, and started tracking big-revenue, small-team AI startups on a website he named the Top Lean AI Native Companies Leaderboard.
“I did some research and found a bunch of companies who all had more than $5 million in [annual recurring revenue], were less than five years old, under 50 employees and growing rapidly,” Shi said.
Since then, Shi says his website has received millions of views. Startups can request to be ranked on the leaderboard, he said, and appearing on it has become a bragging right, as well as a source for potential partnerships, recruiting and investment. To verify the startups’ revenue, Shi said he uses public sources—and in some cases, founders send screenshots of their financial accounts.
Gur, the CEO of Fal, which hosts multimodal generative AI models for developers, said he tracks revenue per head count. Gur has intentionally grown his company from six to 80 employees over the past five years. “Do I think 80 people is super lean? Maybe not,” Gur said. “I think we could be even leaner.”
Weber Wong, founder and CEO of Flora, said the 33-person startup isn’t thinking about “how many heads can we bring onto the team,” but rather how AI agents can supercharge experienced employees.
Some startups, inspired by the lean approach, are actively trimming employees.
“It’s no longer just about growth at all costs, grow your head count as much as possible,” said Deon Nicholas, co-founder and chairman of AI customer service startup Forethought. “It is really about tracking [annual recurring revenue] per employee.”
Forethought, which has about 150 employees, shifted course to become a lean AI startup, Nicholas said. The San Francisco-based startup laid off roughly 30% to 40% of its staff a few years ago. It has since used AI to supercharge its remaining sales, marketing and engineering teams.
“Everyone is more or less producing at, I would say, five to nine times more than they would have been three years ago,” Nicholas said.
Still, there are limitations to staying small.
Being too lean could turn into a “premature optimization around efficiency over growth,” said Theory Ventures’ Tunguz. “The only risk is that the company doesn’t grow as fast as it could conceivably grow, and over time, there is more competition.”
Fal’s Gur said that as the startup began selling to corporate customers, who require more individualized attention, it realized it needed to bulk up its sales team.
“That’s where we’re the least lean,” Gur said. “We realized that you actually need people building those relationships, executing those deals, staying on top of it and taking it across the finish line.”
The risk of not hiring enough can also put small teams under immense pressure. Gur said the startup started hiring more as it realized employees were working long hours and stretched thin.
“If you go back a year and half ago, we were definitely under-resourced, and what that does is you are not able to cater to the market demand,” Gur said.
Write to Belle Lin at belle.lin@wsj.com