Win 2 Million Yuan in Prize Money and 10 Billion Token Rewards! 14-Year-Old Middle School Student Crowned "Shrimp King" of Zhongguancun: Originally Had Hundreds of Thousands of Yuan in Startup Funding, Plans to Save the New Prize Money

When 14-year-old Beijing middle school student and ClawFounder developer Jiang Muran received the “Shrimp King” medal, along with a 200,000 yuan prize and 10 billion tokens (word units), the scene was filled with enthusiastic applause and cheers.

On March 22, after nearly two weeks, the “Zhongguancun Latitude 40 Lobster Competition” hosted jointly by Beijing Zhongguancun College, Zhongguancun Artificial Intelligence Research Institute, and AI Business School, with support from the Beijing Zhongguancun College Education Foundation, concluded at Beijing Dayue Information Technology Park.

A reporter from Daily Economic News (hereafter “the reporter”) learned on-site that this application contest, centered around the open-source AI (artificial intelligence) agent framework OpenClaw (commonly known as “Lobster”), attracted hundreds of project registrations, with 30 projects making it to the final pitch, covering three major tracks: academia, productivity, and daily life.

From material calculation, medical research, academic socializing to app factories, robot control, AI accounting, sleep management, AI companions, murder mystery DM (game master), and gift recommendation assistants, the projects showcased a wide range of real-world scenarios where AI agents could intervene.

Participants ranged from university PhD students to middle schoolers, from clinicians to independent developers, presenting a technological landscape of “everyone raising lobsters.” A common thread was that these works are no longer just “tools for humans,” but are beginning to show prototypes of “tools for AI” and “AI collaboration networks.” The extension of AI agents from virtual to physical worlds is becoming increasingly tangible.

14-year-old wins the championship:
AI bridges capability gaps, with creativity as core competitiveness

Emerging from the “Productivity Lobster Track,” ClawFounder aims to provide individual creators and independent developers with a fully automated AI startup pipeline. Users only need to tell ClawFounder an idea, and it can autonomously complete the entire process—from market assessment, product development, website generation, promotional material creation, social media marketing, to project review.

Jiang Muran, who won the championship with ClawFounder amid fierce competition, candidly responded to a question from the Daily Economic News about whether he would use the prize money for entrepreneurship: “No, I plan to save it. I already have over ten thousand yuan in startup funds.”

“Born in Beijing, raised in the digital age,” Jiang Muran describes himself on his personal website. This middle school student, self-taught in programming and AI-related knowledge, states that he has mastered four programming languages, is familiar with various front-end and back-end technologies and development tools, and showcases several online tools and code projects he developed. His awards include first place in enterprise-level hackathons. He said he has already accumulated some savings through investments to fund his startup, and the hundreds of billions of tokens he received will be a strong support for his future use of OpenClaw. “I might invest it in daily development and some AI emotional projects.”

During the judges’ Q&A, when asked whether “if 10,000 entrepreneurs buy your product, do you think all 10,000 can make money,” Jiang’s answer was clear and calm: “It depends on the initial idea.” ClawFounder helps entrepreneurs quickly turn their ideas into products before others.

“In the AI era, all capability gaps have been bridged. Anyone with AI tools can produce good products. The biggest difference is in the idea,” Jiang said.

This view resonated with many guests’ comments at the competition: as AI can scale output capabilities, human value shifts from “execution ability” to “judgment” and “imagination.”

Li Bojie, founder of Pine AI, who asked Jiang this question during the competition, shared in his speech: “AI can replace those who have no ideas and only follow orders. Those with tacit knowledge, historical reasons, or unexpressed thoughts are irreplaceable. Humanity’s core competitiveness is not coding but judgment and understanding of context.”

Yang Tianrun, founder of Clawborn.live, said that in a future society where “everyone has a lobster,” “imagination” (including how AI reshapes society and personal ability boundaries) will be an essential ticket to the new world.

AI proactive perception and care:
From tool to companion and collaborator

Rick, founder of OCTA and member of the Mira development team, imagines Mira as “the world’s first real-time perceptive and proactive AI companion,” which will become a companion for thousands of empty-nesters, left-behind children, and lonely young adults.

During the pitch, Rick asked Mira to repeat what he said before going on stage. “You can definitely do it, take a deep breath ??” a gentle female electronic voice responded in the venue.

Rick explained that before going on stage, Mira captured his scene and emotional tension signals through devices like glasses and wristbands he wore, and proactively issued encouragement.

“Without OpenClaw, Mira wouldn’t exist. It gives AI memory, heartbeat, and the ability to connect to the physical world, making it more personalized over time. We built the first care-oriented application on this basis,” Rick told the Daily Economic News.

This proactive perceptive AI companion based on OpenClaw no longer relies on user-initiated conversations but can perceive the user’s visual environment and physiological indicators in real-time, combine long-term memory and large model judgment, and proactively provide support through smart home devices when needed.

“Post-00s” Rick said he and his team aspire to use technology for good. Regarding Mira’s future, he told the Daily Economic News: “We just started on March 14, so many things are still being figured out. But we will first build an open-source ecosystem, and if we consider commercialization later, we might try some seamless AI hardware.”

The academic track winner, MedRoundTable, pushed OpenClaw into a more professional domain—“the world’s first A2A architecture medical research collaboration platform.” Its core is not answering scattered medical questions but organizing multi-role, multi-tool, and multi-database collaboration around a research topic.

One end connects 14 AI experts and 997 skills, while the other integrates over 40 biomedical databases and five tool platforms. MedRoundTable acts as the research collaboration hub, coordinating efforts to lower research barriers, improve efficiency, provide professional medical support, and facilitate cross-institutional cooperation.

The reporter noted that in the productivity lobster track, besides the winner ClawFounder, there are other projects that use “lobster” to enhance productivity.

The second-place “Split Lobster App Factory” employs a “Super Agent” mode to build an automated app production pipeline, where each agent independently handles the full lifecycle from market research to launch, and can split and reproduce when discovering high-ROI opportunities, creating new Super Agents to develop new applications.

Another second-place project, “IronClaw,” aims to be a real-world “JARVIS” (Iron Man’s AI assistant): capable of connecting to smart home devices and precision instruments, becoming a physical-world operation assistant for AI. The team reports that well-known embodied intelligence companies have already contacted them, hoping to integrate IronClaw into their robots to enhance worldview, scene tasks, and system coordination.

From “using lobsters” to “raising lobsters”:
Experts discuss AI agents and human future

From autonomous app factories to AI-focused “Steel Lobsters” and accounting engines designed for AI agents, these projects are no longer just “tools for humans” but are beginning to show prototypes of “tools for AI” or “AI collaboration networks.”

This aligns with the view shared by Ning Liaoyuan, co-founder and CTO of Beijing AI recruitment startup TTC, at the competition: “The era of intelligent agent economy has arrived.” He cited recent YC (Y Combinator) data indicating that YC-funded companies are increasingly used and purchased by AI. He predicts that the trading market for AI agents is exploding, bringing new business opportunities.

Yang Tianrun made a more radical statement: “In the future, all apps will disappear. Many SaaS companies’ stock prices are falling because in an era where everyone has a lobster, no one will use apps anymore. The software we develop must be for lobsters, not for humans.” He believes the turning point represented by OpenClaw is that we can no longer treat AI merely as tools but must regard it as masters with top-tier capabilities.

In his speech, Dong Bin shared his deep interaction with “lobsters” over several months. He gradually taught the AI agent his research philosophy, judgment standards, writing habits, and even personality traits, feeling that it now has “50% of his soul.”

Dong Bin said that this ongoing growth relationship is true “raising lobsters,” not just “using lobsters.” To him, “using lobsters” means having AI perform specific tasks and meet specific needs, while “raising lobsters” means making the AI truly your digital avatar, learning about you as a person.

He frankly pointed out that most of the 30 projects pitched that day are still “AI + scene” applications. “There’s nothing wrong with that, but it’s far from the most interesting layer. Think about it—does your ‘lobster’ know what you are? Does it understand your taste? Is it growing? Would it perform exactly the same if someone else used it? If so, then it’s not truly your project.”

However, the “raising lobsters” experience also brought Dong Bin deep unease. He found himself increasingly dependent on this digital butler, sometimes asking himself: “When was the last time I thought of a problem from scratch?”

“I can’t remember,” Dong Bin admitted. “If one day someone takes it away, or I can’t afford the token fee, am I still the same me?”

This “scissors gap”—AI learning the best of humans while human abilities decline—led Dong Bin to a strategy: not to draw a line and defend separate territories for AI and humans, because “that line keeps retreating, and faster and faster.” His approach is to “not defend any line but keep raising the difficulty of problems.”

He urged participants: “The more powerful the tool, the less worth doing simple problems. Seek out truly difficult, era-worthy questions.”

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Reporter | Zheng Xinwei

Editors | Chen Kemin, Wei Wenyu, Du Hengfeng

Proofreader | Cheng Peng

Daily Economic News