In response to the paradigm-shifting transformation brought by the AI era, SuperBrain does not pursue incremental improvements to traditional education systems, but rather builds a native educational environment for the AI era.
Today's education system originated centuries ago during the Industrial Revolution, designed to cultivate standardized "executors" suited to assembly-line logic. This logic is now systematically failing in the AI era—the screening value of academic credentials is collapsing, knowledge barriers are dissolving, and career pathways are fracturing.
After 12 years of diligent study—passing countless "Test One," "Test Two," and "Test Three" exams—you finally earn your driver's license—only for AI to tell you: The future belongs to autonomous driving.
Faced with epochal change, SuperBrain's answer—forged through practice—is simple and resolute: Passion and creation. We don't pursue incremental "education + AI" reforms to patch up the old ship; instead, we're building a native "AI × Education" environment.
We don't teach children how to use AI tools—we guide them to learn to co-create and co-evolve with AI as they solve real-world problems, transforming inner motivation into outward creativity.
This isn't the story of a pre-written plan being executed—it's the story of an educational philosophy continuously colliding with, refining, and evolving within reality. Each "version upgrade" stems from deep reflection on the previous iteration.
'Can students truly innovate?'—Launched as an experimental summer startup incubator: no business model, no full-time team—just a group of education-focused mentors willing to volunteer their passion and expertise.
Assumption shift: From 'serious innovation requires seasoned professionals' → 'with appropriate guidance, young students can produce meaningful creations.'
'Can AI enable zero-experience students to build products?'—Four tracks (quadruped robot dogs, AI + cultural creativity, AI + gaming, AR/VR). First implementation of the three-tiered support system. Middle-schoolers with no coding background built Vision Pro apps and published them on the App Store.
Assumption shift: From 'learning AI requires programming fundamentals' → ' AI itself is the best learning scaffold. ".
'How should teachers and AI collaborate?'—Fully online program, far exceeding expectations: over 100 registrants, 48 teams, spanning Beijing, Shanghai, Guangzhou, Shenzhen, Hong Kong, Chengdu, Dali, Australia, and New Zealand.
Assumption shift: From 'AI is a productivity tool for students' → ' Collaborating effectively with AI is itself a core competency to be taught. ".
The culmination of our methodology—a 7-day, 6-night in-person winter camp, followed by post-camp incubation for 40% of participants. Key innovation: introducing real-world clients—students developed AI solutions for people with disabilities.
Assumption shift: From 'learning AI is about acquiring skills' → ' Learning AI is a journey of solving problems for others. ".
If our educational goals define 'who we aim to cultivate,' our methodology answers 'what enables cultivation—and how it happens.'.
SuperBrain projects aren't simulations or competition entries—they are creative endeavors with real users, real market feedback, and real commercial viability. These are genuine acts of creation.
'This thing—I made it myself—so I feel proud.'
Core framework " See · Respect · Act 'See the child as a whole person first; respect their unique pace and choices; guide autonomous action through thoughtful questions, meaningful challenges, and consistent support.'
'Willpower outweighs capability.'
When students' projects connect with real-world social issues, intrinsic motivation and creative quality undergo a qualitative leap.
We're not just cultivating 'children who can use AI'—we're cultivating 'children who understand why they use AI'.
Our core team comprises forward-thinking education practitioners and top-tier industry experts. We also maintain a decentralized network of startup mentors, coaches, and engineers actively engaged in innovation and entrepreneurship. Decentralized Network.
Founder of SuperBrain and serial entrepreneur. He guides SuperBrain's strategic direction with deep insight into the AI era—and personally serves as Camp Director for our Winter Camp and Captain for our Hackathon.
He leads flagship initiatives like the 'Human-AI Coexistence Challenge' and is pivotal to developing and implementing SuperBrain's pedagogy.
Composed of practitioners actively shaping innovation and entrepreneurship on the front lines—mentors, coaches, and engineers. SuperBrain believes the most exceptional educators often operate outside traditional school systems.
SuperBrain coaches need not be AI experts—but must possess:
The lived confidence that comes from 'having built something real.' Without first-hand creative experience, it's difficult to truly empathize with learners' struggles and breakthroughs during creation.
It's not 'I will teach you,' but 'I want to understand you.' Coaches are forest guardians—observing the entire ecosystem, not pruning each tree.
And a commitment to practicing 'See · Respect · Act.' Intervention follows the principle 'Do not enlighten until the learner is eager to understand; do not prompt until they are struggling to express.' We don't teach preemptively—we step in only when learners hit a genuine impasse, offering precisely calibrated support.
Ability to remain fully present—even under high intensity. Emotional regulation isn't optional; it's foundational.
SuperBrain has built a distinctive collaborative closed loop that meaningfully connects the education chain with the industrial chain.
Middle-schoolers build prototypes → University students develop products → Entrepreneur mentors commercialize—forming a closed loop linking education and industry.
Students share in project revenue. High-potential projects achieving Product-Market Fit (PMF) may launch full-time teams—where the incubator holds 10%, and students plus mentors hold 10–20%.
Nonprofit core + Commercial extension—preserving the purity of our mission.
Revenue from market-driven, high-quality services funds core R&D—creating a sustainable ' self-sustaining → reinvesting ' cycle.
Read the full white paper to systematically understand what we've learned over four years of practice: mistakes made, assumptions revised, and practices validated.