Almost every day, Grant Lee, a Silicon Valley Entrepreneur, hears from investors who try to convince him to take his money. Some have also sent him and his co-founder personal gift baskets.
41 -year -old Lee, normally flattering. In the past, a rapidly growing startup like gamma, an artificial intelligence company that he helped establish in 2020, would have seen out for more money continuously. But today, like many young startups in Silicon Valley, Gama is chasing a different strategy. It is using AI Tools to increase the productivity of its employees in everything from customer service and marketing to coding and customer research.
This means that Gama, which makes software that allows people to create presentations and websites, has no need for more cash, Lee said. His company has hired only 28 people to get the annual recurring revenue and to get “tens of millions” in around 50 million users. Gamma is also beneficial. “If we were from the earlier generation, we would easily be on 200 employees,” Lee said. “We get a chance to reconsider it, originally re -writing the playbook.”
Artificial intelligence at work
The Old Silicon Valley model decided that startups should raise a large amount from venture capital investors and should spend it rapidly in hiring an army of employees. The profit will come much later. Till then, the head count and money raised were badge of respect among the founders who did a philosopher that was very better.
But Gama is one of the growing groups of startups, most of them are working on AI products, which are also using AI to maximize efficiency. They earn money and are growing fast without funding or employees that they will need first. These startups have the biggest argue rights to create the most revenue with the lowest workers. The success stories of “Tiny Team” have now become a meme, sharing the list excitedly with technologies, showing that the anupier, a startup, a startup that makes coding software cursors, hit $ 100 million in annual recurring revenue in less than two years with just 20 employees, and how AII Voice Startup, AII Voice Startup also did the same.
The ability to reduce startups for AI caused wild speculation about the future. Openai CEO Sam Altman has predicted that someday a person of $ 1 billion may be a company. His company, which is building the cost-intensive look of AI, is called a founding model, employs over 4,000 people and has raised more than $ 20 billion in funding. It is also in conversation to raise more money.
With the AI tool, some startups are now announced that they will stop working in a certain size. Finance software company Runway Financial has said that it is planning to top 100 employees as each of its workers will work for 1.5 people. The agency, a startup using AI for customer service, is also planning to hire more than 100 workers.
The agency’s founder Elias Torres said, “This is about ending the roles you do not have when you have small teams.” The idea of AI-operated efficiency was shown in the masses by a Chinese AI Startup by Deepsek, showing that it could manufacture the AI tool for a small fraction of the specific cost. Its success, manufactured on open-source tools that are freely available online, set an explosion of companies that manufacture new products using inexpensive techniques of Deepsac.
“Deepsek was a watershed moment,” said Gaurav Jain, an investor from the above capital, who has supported Gama. “The cost of calculation is very quick, very fast, going down very quickly.” Jain compared new AI Startups Following the wave of companies generated in the late 2000s, Amazon started offering cheap cloud computing services. This reduced the cost of launching a company, causing a hurry to the new startup, which could be made more cheaply.
Jain said that before this AI Boom, startups usually burnt $ 1 million to get $ 1 million in revenue. Now, the cost of up to $ 1 million in revenue exceeds one-fifth and may eventually fall to one-tenth, according to the analysis of the aforesaid 200 startups. “This time, we are only automated to humans opposite data centers,” Jain said.
But if the startups can be profitable without spending too much, this enterprise capital can become a problem for investors, allocating tens of billions to invest in AI startups. Last year, AI companies raised $ 97 billion in funding, which tracks startups, making 46% of all enterprise investment in the United States according to the pitchbook. “Venture Capital works only when you get money in the winners,” otherwise an investor Terence Rohan with funds said, which focuses on a very young startup.
