13-year-old with no coding background earns $2,600 in 3 days with AI study app

The app and how it works

Zhu Shuhan, a 13-year-old student from Shanghai, built an AI-powered app called Zai Chang (“On Site”) to help parents supervise their children’s homework remotely. The app takes a photo of a parent uploaded by the user and turns it into a virtual avatar displayed on the child’s screen.

During study sessions, the app uses a camera to monitor the child’s behavior. If it detects distractions—like leaving the seat or using a mobile phone—the virtual parent delivers a voice reminder. After the session, the app generates a concentration report for the parent.

How the app earned $2,600 in three days

Shuhan presented Zai Chang at a national AI product marketing competition in Hangzhou, held from August 21 to August 23, 2026. The competition’s judging criteria were unusual: instead of evaluating technical merits, it required participants to prove people would pay for their products.

Zai Chang received 90 orders and generated 18,000 yuan (about $2,600) in sales during the three-day event. This performance earned Shuhan third place and a 5,000-yuan cash prize, according to YourStory.

Why this matters for founders

Shuhan had no programming background and began using AI tools only a year before building the app. Her story highlights how AI is reducing the technical barriers to creating functional prototypes. Founders no longer need years of coding experience to test an idea, though understanding the problem and validating demand remain critical.

The competition’s focus on sales over technical sophistication underscores a key lesson: a product’s success depends on whether people are willing to pay for it, not just how well it is built. For founders, this reinforces the importance of early customer validation and willingness-to-pay metrics.

The app also raises practical questions about privacy and responsible development. Zai Chang uses camera monitoring, which requires parental consent and careful data handling. Founders building products that involve surveillance or child safety must prioritize transparency and compliance to avoid regulatory or reputational risks.

What this means

Lazyfounder analysis — our interpretation, not reported fact.

Zhu Shuhan’s story shifts the conversation for founders and operators about what it takes to build and validate a product today.

1. AI lowers the technical barrier to entry: Shuhan had no programming background but used AI to create a functional prototype. This signals that founders no longer need deep technical expertise to test ideas—AI tools can bridge the gap, at least for early versions. However, the story also shows that technical skills are only one part of the equation.

2. Validation over perfection: The competition rewarded sales, not code quality. This is a useful reminder for founders: a product’s success depends on whether people will pay for it, not just how well it’s built. For operators, this reinforces the value of early customer feedback and willingness-to-pay metrics over polished features.

3. Problem-driven over tech-driven: Shuhan started with a real problem—parents wanting to supervise homework without being physically present. This highlights why founders should focus on pain points rather than technology for its own sake. The app’s success came from addressing a specific need, not from being the most advanced AI solution.

4. New considerations for young founders: For young entrepreneurs, especially in markets like India where parental supervision of education is a cultural norm, stories like this could inspire similar experiments. However, it also raises questions about responsible development, particularly around privacy and consent when building products that involve surveillance. Operators in edtech or family-focused startups may need to adopt stricter data-handling practices to avoid backlash.

5. The role of competitions as validation: The competition’s format—prioritizing sales over technical judging—shows how startup contests can be used as a low-risk way to test demand. Founders could consider similar events as a way to validate ideas before scaling.