Answer-Box: At the 2026 WAVES conference in Guangzhou, industry leaders discussed the rise of One Person Companies (OPCs) in the AI era, noting that cloud platforms now see more non-developers than coders. A survey by Alibaba Cloud in February 2026 found that only 20% of its users were traditional developers, while 35% were product or operations professionals and 21% were business owners, signaling a shift in cloud computing's user base. The panel highlighted that AI tools enable individuals to achieve near-corporate productivity, with OPCs leveraging code and media as low-marginal-cost levers.
The Evolution from Street Vendor to Digital Solopreneur
The panel drew parallels between the individual entrepreneurs of the 1980s-90s, who operated from a tricycle stall, and today's OPCs. While both lower the barrier to starting a business, the underlying mechanics have fundamentally changed. Past individual businesses relied on physical labor, location, and experience—essentially local services tied to a specific spot. Today's OPCs, by contrast, use code and media as leverage, with AI democratizing production capabilities. As Wang Zijian, founder of Zhima Finance (an OPC itself), put it: an OPC is a super individual plus AI tools and an external collaboration network, backed by cloud services, AI models, and infrastructure.
He Chuan, head of product operations and ecosystem cooperation at Alibaba Cloud's elastic computing division, pointed to three key differences. First, the trigger: past reforms were policy-driven, while today's shift is technology-driven. Second, business scope: old vendors were location-bound, but a modern OPC can reach customers across the entire internet. Third, leverage: following Naval Ravikant's framework of labor, capital, code, and media, the latter two now have near-zero marginal cost, allowing OPCs to scale beyond traditional limits once they achieve initial traction.
How AI-Powered OPCs Actually Make Money
Wang Zijian shared his own OPC experience running a GEO (Generative Engine Optimization) service that helps companies get their brand information into AI knowledge bases. Previously, this work would require a team of 5 to 10 people; now he handles it alone using tools like ChatGPT for logos, Variant and Replit for websites, and Codex or Claude for backend development. He emphasized that while repetitive tasks should be delegated to AI, strategic decisions—like which product to prioritize—must remain with the founder. "Repetitive work goes to AI; time is freed for high-value decisions," he said.
Zhan Zhicheng, director of innovation and entrepreneurship at the Guangzhou University Town Technology Transfer Center, noted that student OPCs typically focus on four areas: AIGC digital content, AI-powered cross-border e-commerce, AI in smart healthcare (such as exporting traditional Chinese medicine knowledge), and AI-hardware integration. Student teams are small—usually one to three people—and often cross-disciplinary, combining engineering from South China University of Technology with design from Guangzhou Academy of Fine Arts. The local government supports them with free office space, funding, and subsidized computing power.
The Infrastructure Behind One-Person Companies
A key theme was that while AI makes starting easy, scaling requires robust systems. He Chuan described a "15-degree angle" concept: an OPC's direction should be slightly offset from large models to avoid being subsumed by them. However, OPCs and platforms are not inherently competitive—OPCs excel in niche, deep verticals, while platforms handle broad, standardized solutions. Alibaba Cloud has simplified its offerings into staged packages (Starter, Lite, Professional) to match OPCs' growth from a simple website to high-availability, secure systems.
Li Ercheng, general manager of product planning at Intel's Data Center Group, explained that from idea to demo to a sustainable business, there is a huge gap that infrastructure must bridge. In the agentic era, CPUs handle orchestration and coordination while GPUs focus on computation. Intel works with cloud platforms to optimize the underlying technology so that individual founders can benefit from enterprise-grade reliability without needing to manage it themselves. The goal is to let founders concentrate fully on strategy and creativity, while the system handles SLA guarantees and customer retention.
Breaking Through the Scaling Bottleneck
Wang Zijian identified the hardest phase not as acquiring the first customer, but as avoiding the reflex to scale by hiring more people once orders increase. To sustain growth, he advocates three principles: productizing services, using AI efficiency tools, and standardizing processes. He maintains a daily video update by feeding his workflow to an AI agent that generates scripts, covers, and tags, doubling efficiency.
He Chuan added two pieces of advice from his experience. First, product development: the first version is usually disliked by more people than like it. Good product managers persist and shorten the iteration cycle by constantly adjusting based on customer feedback. Second, go-to-market efficiency determines an OPC's ceiling and scaling cost. After AI democratizes basic capabilities, the real differentiator becomes how well you refine the product experience and amplify its reach.
Zhan Zhicheng observed that student OPCs often get stuck on order acquisition and delivery stability. The university community helps by matching them with suitable projects and providing credibility, while offering free or subsidized computing power through campus data centers. Li Ercheng reinforced that while AI simplifies the top layer, the underlying compute and platform technology must become increasingly sophisticated to keep the founder's burden light.