Starting a business at 18 and raising funds at 19: Amid the AI wave, a group of young people are leaving the classroom early.
Recently, Business Insider interviewed 16 artificial intelligence entrepreneurs in the "Young Geniuses" special feature. What's most striking about the report isn't the scale of financing, but the age of the founders: many are under 25, and several are even under 20.
The products developed by these young people cover multiple fields such as learning tools, content creation, medical systems, and consumer applications. Some have already secured millions of dollars in financing, and some products have started generating stable revenue. More importantly, many entrepreneurs are doing the same thing: pausing their studies, leaving campus, and devoting all their time to AI startups.
01
The AI window period has emerged,
and some young people are taking early action
For a long time, technical talents have generally followed a relatively stable growth path: entering university to learn professional knowledge, then joining companies or research institutions to accumulate experience, and finally having the possibility of starting a business.
However, in the wave of artificial intelligence, this path is being rewritten. Some young people are entering the industry earlier and making decisions related to their learning paths earlier. For the education industry, this change is worth observing carefully because it is influencing students' understanding of technology, learning, and future career paths.
Among this group of entrepreneurs, 18 - year - old Zach Yadegari is the youngest. He started developing applications in high school and sold one of his game applications at the age of 16, earning nearly $100,000. Subsequently, he and his team launched the AI diet management app Cal AI, which analyzes users' diet data through artificial intelligence and provides them with nutritional advice.
According to the report, this app has achieved an annual revenue of approximately $30 million in just over a year and has a team of dozens of people.
Another entrepreneur, 18 - year - old Arlan Rakhmetzhanov, chose to drop out of high school and enter the startup accelerator Y Combinator to found an AI code agency. He applied to YC three times in a row before being admitted and finally received investment to start his business.
Similar situations keep appearing in the report. 24 - year - old Carina Hong paused her graduate studies at Stanford to found the AI company Axiom Math and secured $64 million in seed - round financing. Two students who had just entered the Massachusetts Institute of Technology chose to leave campus to found an AI policing technology company. Some entrepreneurs took a gap year from Harvard University and focused on their startup projects in San Francisco.
The common background behind these choices is that the artificial intelligence industry is in a stage of rapid development.
In the past few years, breakthroughs in large - model technology have driven the rapid improvement of artificial intelligence capabilities. Capabilities such as image generation, text generation, and code generation have gradually matured, and a large number of new application scenarios have emerged. Many investment institutions and entrepreneurs believe that the current AI industry is still in its early stage, the industry structure is not yet stable, and new products and companies still have the opportunity to grow rapidly.
In such an environment, the pace of entrepreneurship has accelerated significantly. Teams often hope to enter the market as early as possible and find the matching relationship between products and needs through continuous iteration.
This phenomenon is not the first time in the history of technology. Similar stages were experienced in the early days of the Internet and the early days of the mobile Internet. When technological capabilities are advancing rapidly and the industry structure is not yet stable, entrepreneurial activities tend to increase significantly.
The rapid development of artificial intelligence has made a similar window period appear again. Some young people's choice to take early action is a direct response to this opportunity.
02
The AI application layer is booming,
and small teams can quickly enter the industry
Observing the directions of these startup projects, we can find that most of them are concentrated in the AI application layer.
In recent years, the development of large - model technology has been mainly driven by large technology companies and research institutions. At the same time, more and more development interfaces and open - source tools are being made available to developers, enabling small teams to build products on the basis of these technologies.
In the report, 20 - year - olds Rudy Arora and Sarthak Dhawan developed an AI classroom note - taking tool called Turbo AI during their university years. This product can automatically record classroom content and generate study notes, helping students organize course information. According to the report, the app adds about 20,000 new users every day and is expected to achieve eight - figure annual recurring revenue.
Similar products have also emerged in the content creation field. 21 - year - old Jay Neo founded the AI creator assistant Palo. This tool analyzes the creator's past video content and generates new short - video scripts and content structures for creators, aiming to improve content production efficiency.
AI applications have also appeared in the medical and public service fields. 19 - year - olds George Cheng and Dylan Nguyen founded the company Code Four, which uses artificial intelligence to analyze police body - camera videos and automatically generate law - enforcement reports and text records, thereby reducing the time police officers spend on paperwork.
Another startup, Novoflow, has developed an AI system for medical institutions to help clinics handle appointment, cancellation, and management processes.
These projects cover different industries, but their technical paths are very similar: using existing artificial intelligence capabilities to build specific applications.
This structure is somewhat similar to the application innovation stage in the early days of the Internet. After the basic technology matures, a large number of startup teams will develop products around various niche scenarios. Different teams try different directions, and new product forms keep emerging.
The development of artificial intelligence is driving a similar process. As development tools and open - source models become more and more mature, small teams can complete product development in a relatively short time and quickly test market feedback.
This is why many startup teams are small in scale and the age of the founders is significantly lower. The change in the technical threshold has given young developers more opportunities to try.
03
The starting point of technology is moving forward,
and the education system is facing new problems
Another common feature in the growth experiences of these entrepreneurs is that they generally started contacting technology at an early age.
In the report, some entrepreneurs started learning programming in their childhood. For example, Zach Yadegari attended a programming summer camp at the age of 7 and started contacting code from then on. Some entrepreneurs learned programming through the Internet in middle school and developed their own applications in high school.
This situation was not common in the past. Programming usually only entered professional courses at the university level, but now, a large number of online courses, open - source projects, and development communities allow students to contact technology at an earlier stage.
The change in the technology learning environment has enabled some students to have quite mature programming skills when they enter university. For them, university is no longer the starting point of technology learning but a stage to continue exploring technology directions.
At the same time, AI tools are also changing the development mode. AI programming assistants, automated code - generation tools, and open - source models have significantly improved development efficiency. Some work that originally required a team can now be completed by a few developers.
This change has continuously advanced the starting point of technological innovation. Some students can participate in real projects or even directly enter the startup ecosystem during their university years.
For the education system, this change brings new problems. The classroom is still an important place for systematic learning, but the channels for students to acquire technical knowledge have increased significantly. Online communities, open - source projects, and startup teams have all become important environments for technology learning.
In recent years, some universities have begun to adjust their curriculum structures. Project - based learning has gradually increased, and students conduct practice through real - world problems; interdisciplinary courses have also increased, aiming to establish a closer connection between technology learning and industry needs.
The development of artificial intelligence has not only changed the industrial structure but is also gradually changing the growth path of talents. The problem that the education system needs to face is not just whether students will enter the technology industry, but how to continue to play a role in the new technological environment.
It's still difficult to judge whether these young AI entrepreneurs will be able to build long - term successful companies in the future. Entrepreneurship itself is full of uncertainties, and most projects still need to undergo long - term market tests.
However, their emergence has already shown one thing: the technological environment is changing the time when talents enter the industry. When development tools become more mature and technical resources become more open, some young people can contact technology, develop products, and participate in industrial innovation earlier.
For the education industry, this change is not simply a competitive relationship but a new reality. Students are contacting technology earlier and their learning paths are becoming more diverse. The classroom is still important, but it is no longer the only starting point.
When more and more students have contacted programming, participated in projects, or even developed products before entering university, the education system needs to rethink its role: how to help students understand technology, apply technology, and find their direction in the rapidly changing technological era.
The development of artificial intelligence continues, and the rhythm of talent growth is also changing. How education responds to this change will be an unavoidable issue in the coming period.
Original link:
These 16 AI startup founders have raised over $100 million in total — and they're all under 27.
https://www.businessinsider.com/young-founders-raising-millions-for-their-ai-startups-2025-12
This article is from the WeChat official account "Duojing" (ID: DJEDUINNO). The author is Siluo, and it is published by 36Kr with authorization.