A group of post-00s entrepreneurs are making unprecedented waves in the field of AI. From interns to CEOs of tens of billions of dollars, they have rapidly risen in the AI wave in just a few years or even months with their keen insight and excellent technical capabilities, rewriting the rules of entrepreneurship and showing the vigorous power and infinite possibilities of the younger generation.
In this global entrepreneurial wave detonated by AI, a group of young people born after 2000 are rushing to the forefront at an astonishing speed.
Some people went from interns to CEOs of companies valued at nearly $10 billion in three years; some people lead a small team of less than 30 people to create an AI recruitment platform with a monthly profit of one million dollars; Others made $2.2 million in 50 days with a cheat tool, and then backhanded the establishment of an AI company to win venture capital financing.
The youngest of them is only 18 years old, and the oldest is only 25 years old, but they have created staggering numbers:
The 3-year valuation is $9.9 billion, the annual revenue of the 4-person team exceeds $12 million, the 23-person team raises $465 million, and the 0-product valuation is $500 million……
This is not an accident, but the birth of a new order. These post-00s AI entrepreneurs are defining the new entrepreneurial rules of the AI era:
(1) Programming is their mother tongue and the starting point for AI entrepreneurship;
(2) Most of them became famous at a young age, and in an era when the technological dividend window was extremely compressed, young people became the first to seize the opportunity;
(3) They grew up in the flood of information and sensed “where the needs come from” more keenly than any other generation;
(4) They have a completely different understanding of “organization” and “product”: the product is AI, not “+AI”; It is more inclined to build a minimalist and efficient team, replacing manpower with technology and replacing hierarchy with systems.
It is these seemingly “generational differences” details that make us more convinced:
The future of AI does not just belong to them, but is created by them.
01 From an intern to the CEO of a $10 billion company, it only took 3 years for the strongest post-00s
Three years ago, he was an intern with no formal work experience. Three years later, he was at the forefront of the global AI wave and became the CEO of a $10 billion AI startup.
This is the story of Michael Truell, founder of Anysphere (Cursor).
To achieve these three challenges, product managers will only continue to appreciate
Good product managers are very scarce, and product managers who understand users, business, and data are still in demand when they go out of the Internet. On the contrary, if you only do simple communication, inefficient execution, and shallow thinking, I am afraid that you will not be able to go through the torrent of the next 3-5 years.
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Michael Truell, born in 2000. In high school, Michael Truell has already won the ACM/CSTA Cutler-Bell Award for his technical excellence and won a medal in the International Informatics Olympiad (IOI).
During his college years, he interned at top companies such as Google, Two Sigma, Octant, and also worked as a researcher at MIT. However, he did not choose a “standard” route of the tech elite.
In 2022, he and three MIT classmates – Sualeh Asif, Arvid Lunnemark, and Aman Sanger – saw that AI would reshape the way developers work, teamed up to launch Anysphere and launch its core product, Cursor, an AI programming assistant.
As soon as this product was launched, it caused a huge sensation.
In its first full year after launch, Cursor’s ARR (annual recurring revenue) exceeded $100 million. Subsequently, it turned on the “crazy growth” mode – almost doubling every two months. After reaching $300 million ARR in April 2025, it has exceeded the $500 million mark in just two months. It is now used by more than half of the Fortune 500 companies, including Uber, NVIDIA, and Adobe.
What’s even more amazing is that Cursor’s net revenue retention rate (NDR) is as high as 200%, setting a new high in the SaaS industry. In its latest funding round, Cursor completed a $900 million Series C funding round led by Thrive, soaring to $9.9 billion in valuation and stepping into the 10 billion club.
Cursor’s story has just begun.
02 Three post-00s who dropped out of school created a 10-billion-level AI recruitment unicorn in 24 months
In 2022, three 18-year-old college students started an experiment of “no money but don’t want to work” in the dormitory; Two years later, the experiment became Mercor, an AI recruitment platform with a valuation of $2 billion and customers including OpenAI.
This is the story of the three co-founders of Mercor.
Mercor’s three co-founders – CEO Brendan Foody (born in 2004), CTO Adarsh Hiremath, and COO Surya Midha – are all 21 years old and have dropped out of school. In high school, the three won the debate competition together. Later, he was admitted to Harvard and Georgetown University respectively, but chose to take a leave of absence in his sophomore year and typed out the first version of the Mercor prototype in the dormitory. Initially just a small matchmaking platform for Indian engineers, it achieved monthly revenue of $100,000 and profit of $80,000 within half a year.
Mercor is not a traditional recruitment website that “posts jobs and sends resumes”, but an AI-powered automated recruitment system. After uploading a resume, job seekers need to complete a 20-minute video interview with AI. After the recruiter uploads the job information, the system will automatically complete all processes such as matching, recommendation, and screening. It’s like talking to a business-savvy headhunter instead of mechanically brushing forms.
At present, the Mercor platform has more than 460,000 active job seekers, covering development, design, operation, analysis and other positions. Companies pay commissions to the platform based on their annual salary, usually 30% of their salary, and their customers include tech giants such as OpenAI and Founders Fund.
According to Brendan, Mercor will grow at an average monthly rate of 41% in 2024, 5% in January this year, and 88% in February, with a monthly profit of more than $1 million in February.
In February, Mercor completed a $100 million Series B funding round, and its valuation soared to $2 billion from $250 million five months ago, an eight-fold increase. In the AI recruitment track, this speed is historic.
03 Joined Meta to do AI in high school, founded Magic at the age of 25, and raised more than $400 million in just two years
In 2022, a 22-year-old Cambridge dropout joined forces with a German CTO to found an AI coding company; Two years later, the company has fewer than 25 employees, but has received a total of $465 million in financing from giants such as NVIDIA, Sequoia, and Alphabet, with a valuation of $1.5 billion.
It’s called Magic, and one of the founders is the post-00s – Eric Steinberger.
Steinberger was born in 2000 and is from Vienna, Austria. At the age of 14, he taught himself programming and physics through MIT online classes, and then volunteered to join Meta in high school, collaborating with OpenAI o1 core researcher Noam Brown on AI research. At that time, he was not yet an adult, but he was already on the front line of AI scientific research. Later, he was admitted to the Department of Computer Science at the University of Cambridge, dropped out of school after only one year, and officially started his entrepreneurial career.
In 2022, he founded Magic with Sebastian De Ro, former CTO of German process management platform FireStart, with a clear goal: to create AI tools that can actually write code for programmers.
The core positioning of Magic is not to simply complete the code, but to allow AI to understand, generate, modify, and debug the entire program. In 2024, they released the world’s first large model with a 100 million Tokens context window**, LTM-2-mini, which can handle hyperscale project code and retain context and logic throughout the process.
In less than two years, Magic has completed three funding rounds:
- In the summer of 2022, Magic completed a $5 million seed round of financing;
- In February 2023, Magic announced the completion of a $23 million Series A financing.
- In February 2024, it received $117 million in financing, led by NFDG Ventures, and co-investors include CapitalG and Elad Gil;
- In June 2024, it received another $320 million in financing, led by former Google chairman Eric Schmidt, when the company’s team had only 23 people;
So far, it has raised a total of US$465 million and is valued at US$1.5 billion, making it one of the projects with the fewest employees and the highest financing density in the AI tool track.
04 AI thinks like a mathematician, but it is valued at hundreds of millions of dollars without a product
Last week, a post-00s girl suddenly became popular among AI investors.
Her name is Hong Letong. The cause is a report by The Information:
Axiom, an AI startup with 0 products and 0 customers, and does not even have an official website, is raising $50 million with a valuation of about $300 million to $500 million. Its main direction is to let AI solve the most difficult mathematical problems.
Although Hong Letong quickly denied the financing information on social platforms, saying that the report was inaccurate. But it still doesn’t affect her and Axiom getting enough attention.
Hong Letong was born and raised in Guangzhou, studied at the famous High School Affiliated to South China Normal University, and won medals in the Mathematical Olympiad many times. He was later admitted to the Massachusetts Institute of Technology and graduated from Oxford University with a master’s degree.
Before graduating, she won the Schafer Award for Excellence in Mathematics (the highest award among MIT undergraduate girls), and before graduating, she won the Morgan Prize, the highest honor for undergraduate mathematics in North America, making her the fifth female student in history to receive the award.
Today, Hong Letong is planning to apply his mathematical abilities to the field of AI. Axiom’s vision is for AI to not just generate answers, but to truly understand the problem, build logic, write proofs, and give 100% rigorous conclusions. Axiom’s early client targeting is precise: hedge funds, quant companies. Because the large number of problems that these enterprises deal with on a daily basis are essentially complex and dynamic mathematical modeling processes. Allowing AI to participate in modeling and formal analysis will greatly improve the efficiency and accuracy of trading strategy research and development.
05 The post-00s are in action: from the world’s largest AI application platform to earning 56 million yuan by shell AI
In addition to the above post-00s who have raised tens of millions of dollars at every turn, we can also see many post-00s entrepreneurs active in various AI segments.
Dang Jiacheng, who was born in 02, has created the world’s largest open source AI application platform FlowGPT, which has achieved millions of monthly active users and more than 100,000 AI applications, and has also received multiple rounds of investment from DCM and Goodwater.
Zach Yadegari, 18, and Blake Anderson, 23, have made Cal AI, a calorie-tracking AI app. As soon as Cal AI was launched, it showed super earning power. One month after its launch, Cal AI’s monthly revenue exceeded 1 million, and it increased month by month. By the end of last year, Cal AI’s ARR reached $8 million.
and Roy Lee, a post-00s college student who made $2.2 million in less than two months by selling his own AI cheating tools, and was then expelled from Columbia University.
Today, not only has he not disappeared, but has become the object of venture capital. A few days ago, Roy Lee announced that his AI company Cluely received US$5.3 million (about 38.68 million yuan) in seed round financing.
In addition to foreign countries, the domestic post-00s generation has also begun to emerge in the field of AI.
Yang Fengyu, born in 2000, studied computer science at the University of Michigan as an undergraduate, and then entered Yale University to study for a CS doctorate, focusing on embodied intelligence. After graduating with a doctorate, he did not stay in a major American technology company, but returned to China and founded a embodied intelligence company – UniX AI.
UniX AI’s first product is a humanoid robot with human-like behavior capabilities and wheeled movement, focusing on “mass production” and “industrial landing”. Unlike many conceptual robot projects, UniX AI will be manufactured in Suzhou in 2024 and is expected to begin mass shipments.
Chen Yuanpei, co-founder of Lingchu Intelligence, is also a post-00s generation who is obsessed with robots and studied under Professors Karen Liu and Li Feifei as a visiting scholar at Stanford.
06 Four key characteristics of post-00s AI entrepreneurs
(1) Programming is their way of understanding the world and a general problem-solving ability.
For this generation of entrepreneurs, programming is no longer just a technical skill, but a cognitive tool. They express themselves in code, experiment, build products, and directly enter the business with technology.
Michael Truell (Cursor) built the programming platform Halite in high school; Eric Steinberger has taught himself programming through MIT online classes since he was 14 years old; Anderson had already made two AI products before developing Cal AI. Technology has never been a shortcoming of “finding someone to make up for it”, but the starting point of their entrepreneurship.
(2) In the AI era, become famous as soon as possible.
When the technical dividend window continues to compress, the time node for young people to come out continues to move forward.
Before the summer of his freshman year was over, Michael Truell had been spotted by Ali Partovi (an early investor in Facebook, Airbnb, Dropbox) and became a member of the Neo Talent Program, who also invested in his company, Anysphere.
14-year-old Eric Steinberger, before entering college, took the initiative to contact Noam Brown, a top AI researcher at Meta (later a core member of OpenAI o1), to get research opportunities; Brendan Foody, born in 2004, founded his first digital consulting firm in high school.
This is not accidental, but a true portrayal of the rhythm of the AI era:
The technical dividend window is getting shorter and shorter, young people can do more and more, and the famous “time zone” is moving forward.
This is why Roy Lee is still sought after by venture capitalists after earning 2.2 million in 50 days and detonating controversy; Hong Letong is still studying for a doctorate, and the company can raise funds at a valuation of 3-500 million.
(3) They grew up in the flood of information and better understood “where the demand comes from”.
This generation of entrepreneurs does not look for tracks from macro data or expert reports, but directly plunges into communities, platforms, and social networks where users are active, and finds opportunities from demand fragments.
Dang Jiacheng founded FlowGPT because he saw a large number of users spontaneously sharing prompts on Discord and Twitter, and also formed a community form similar to the early GitHub, so he quickly launched the product and became an instant hit.
Before doing Cal AI, Zach keenly discovered that “calorie tracking” had more than 147 million hashtags on TikTok, and was included in the company’s employee health plan, decisively cutting into the trend of healthy eating, and achieving millions of dollars in monthly revenue within a month.
The topics chosen by this generation of entrepreneurs are not top-down business propositions, but real scenes captured from the bottom up.
(4) They are rewriting the definitions of “organization” and “product”.
Rather than saying that these post-00s AI entrepreneurs are just young, they represent the starting point of another technological culture. They are not imitating Silicon Valley, but taking the initiative to propose new organizational forms and product paradigms in a native AI environment.
Their understanding of “organization” is a minimalist but efficient structure, almost unanimously pursuing a structure of small teams, strong execution, and fast iteration:
- When Magic was valued at $1.5 billion, the team had only about 23 people;
- Mercor has an annual income of $75 million and a team of only about 30 people;
- Cal AI is more extreme, with a team of 4 people alone to make an ARR of $12 million;
- Despite its rapid growth and valuation of tens of billions, Cursor still maintains a compact structure of 40-60 people.
These teams reject redundancy, flat organizational structures, universal remote distribution, and combat units that emphasize “one person is one module”. Compared with traditional enterprises, “large numbers” are not a moat in their eyes, but a variable that slows them down.
In terms of product understanding, they also consistently demonstrate the AI-native product philosophy: not “+AI”, but product logic that was born for AI from the beginning.
Mercor, for example, has automated its entire recruitment process, and the founders believe that “Chat is the core of all future UIs”, and the original version was a recruitment platform built around the chat interface.
They presuppose a future where web buttons disappear, people simply tell the AI what to do, and the system automates all interactions.
Cursor further reconstructs the IDE: it is not an “editor that integrates AI”, but “AI is an editor”. Through natural language expression of intent, developers no longer click commands and write functions, but let AI reconstruct code logic based on semantic understanding.
This is not only an efficiency revolution, but also a paradigm revolution:
- from command-driven to intent-driven;
- From AI plug-ins to AI is the product itself;
- From AI-assisted enhancement to AI-led operation logic.
From Cursor to Magic, from Mercor to Axiom, this group of rising post-00s entrepreneurs has brought far more than the word “young”. More essentially, it is an intergenerational switch of the underlying way of thinking. They are not only using AI to build new products, but also using AI to rewrite the rules of entrepreneurship.
And this is precisely the most certain and non-negligible sense of direction in this wave of AI entrepreneurship.
