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Almost every day, Grant Lee, a Silicon Valley entrepreneur, hears from investors who try to persuade him to take their money. Some have even sent him and his co-founders personalized gift baskets. Mr. Lee, 41, would normally be flattered. In the past, a fast-growing start-up like Gamma, the artificial intelligence start-up he helped establish in 2020, would have constantly looked out for more funding.
But like many young start-ups in Silicon Valley today, Gamma is pursuing a different strategy. It is using artificial intelligence tools to increase its employees’ productivity in everything from customer service and marketing to coding and customer research. That means Gamma, which makes software that lets people create presentations and websites, has no need for more cash, Mr. Lee said. His company has hired only 28 people to get “tens of millions” in annual recurring revenue and nearly 50 million users. Gamma is also profitable.
The old Silicon Valley model dictated that start-ups should raise a huge sum of money from venture capital investors and spend it hiring an army of employees to scale up fast. Profits would come much later. Until then, head count and fund-raising were badges of honor among founders, who philosophized that bigger was better.
But Gamma is among a growing cohort of start-ups, most of them working on A.I. products, that are also using A.I. to maximize efficiency. They make money and are growing fast without the funding or employees they would have needed before. The biggest bragging rights for these start-ups are for making the most revenue with the fewest workers.
Stories of “tiny team” success have now become a meme, with techies excitedly sharing lists that show how Anysphere, a start-up that makes the coding software Cursor, hit $100 million in annual recurring revenue in less than two years with just 20 employees, and how ElevenLabs, an A.I. voice start-up, did the same with around 50 workers.
The potential for A.I. to let start-ups do more with less has led to wild speculation about the future. Sam Altman, the chief executive of OpenAI, has predicted there could someday be a one-person company worth $1 billion. His company, which is building a cost-intensive form of A.I. called a foundational model, employs more than 4,000 people and has raised more than $20 billion in funding. It is also in talks to raise more money.
With A.I. tools, some start-ups are now declaring that they will stop hiring at a certain size. Runway Financial, a finance software company, has said it plans to top out at 100 employees because each of its workers will do the work of 1.5 people. Agency, a start-up using A.I. for customer service, also plans to hire no more than 100 workers.
The idea of A.I.-driven efficiency was bolstered last month by DeepSeek, the Chinese A.I. start-up that showed it could build A.I. tools for a small fraction of the typical cost. Its breakthrough, built on open source tools that are freely available online, set off an explosion of companies building new products using DeepSeek’s inexpensive techniques.
For now, investors continue to fight to get into the hottest companies, many of which have no need for more money. Scribe, an A.I. productivity start-up, grappled last year with far more interest from investors than the $25 million it wanted to raise.
Some investors are optimistic that A.I.-driven efficiency will spur entrepreneurs to create more companies, leading to more opportunities to invest. They hope that once the start-ups reach a certain size, the firms will adopt the old model of big teams and big money.
Some young companies, including Anysphere, the one behind Cursor, are already doing that. Anysphere has raised $175 million in funding, with plans to add staff and conduct research, according to the company’s president, Oskar Schulz.
Other founders have seen the perils of the old start-up playbook, which kept companies on a fund-raising treadmill where hiring more people created more costs that went beyond just their salaries.
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