Entrepreneurship is becoming increasingly "light." No need to gather partners, no need to build complex teams—one person or a few people, with the help of AI tools, can open a legitimate limited company. This entrepreneurial model called OPC (One Person Company) is quietly becoming a new choice for many. It offers ordinary entrepreneurs, freelancers, technical professionals, and niche-track entrepreneurs a freer, more legitimate, and more flexible new path. For this reason, the number of OPCs in China is steadily rising, becoming a new force for stabilizing employment and activating the individual economy. The state continues to optimize the business environment, constantly loosening restrictions and empowering this new entrepreneurial model. But when mentioning OPC, many people's first impression is content tracks like short dramas and self-media. After an on-site visit to Hebei's first OPC community—the Qingyan Shuzhi Artificial Intelligence OPC Community located in Shijiazhuang—one finds that the ways to play OPC are far richer than imagined.

Where is the soil for OPC in Hebei?

Hebei has many county-level characteristic industrial clusters—luggage, wire mesh, textiles, traditional Chinese medicine, equipment manufacturing, and so on. Ge Zhi, operations head of the Qingyan Shuzhi Artificial Intelligence OPC Community, told reporters, "The solid foundation of the real economy has become the biggest soil for developing industrial OPC in Hebei." Industrial OPC is not about hiding online making virtual content; rather, small technical teams transform into digital "special forces," taking root in industrial clusters and directly confronting the real pain points of factories and enterprises. "When traditional large enterprises undertake digital transformation, building a full team in-house is costly, and the price of trial and error is enormous," said Ge Zhi. "As the smallest trial-and-error unit, industrial OPC enters in a lightweight manner with small teams, first conducting small-scale verification, then expanding implementation after running through the process, helping the real economy reduce the cost of digital trial and error." The model insists on "first having a scenario task, then matching the OPC." The community holds real demands from the industrial side, then matches corresponding small teams to undertake tasks based on the capability matrix of dozens of resident enterprises. Entrepreneurs are not encouraged to brainstorm ideas out of thin air, but to develop based on the real needs of the real economy.

Is OPC an exclusive arena for young people?

Many people believe that as a new entrepreneurial model deeply tied to AI, OPC must be the home turf of young people. But at the Qingyan Shuzhi Artificial Intelligence OPC Community, reporters saw different faces. Zhao Hao, who is over fifty, and Zheng Ganghua, with several young people, are working on a brain-computer interface transformation project at Hebei Qidong Brain-Computer Interface Technology Co., Ltd. In this company, these two are the absolute core. "OPC is not a patent of young people. Our community is positioned as industrial OPC, and we have never set age or educational thresholds for entrepreneurs," said Ge Zhi. What truly distinguishes whether one can do industrial OPC well is not age, not a diploma, but three things: deep industry accumulation, continuous independent learning ability, and the ability to organize and dispatch multiple AI agents to solve real industrial problems. Zhao Hao has deeply cultivated big data and artificial intelligence for many years, fully responsible for project operations and industrialization implementation; Zheng Ganghua has a background in algorithms and large model development, having done smart city and government informatization projects in earlier years, and is currently the company's technical director. The industry judgment and experience in solving real problems that these two have accumulated are precisely the qualities that industrial OPC values most.

Is OPC just one person fighting alone?

Many statements online describe OPC as "one person, one computer, making money from home." "Many people mistakenly think OPC is just self-employment, one person fighting alone. Actually it's not," said Ge Zhi. OPC is not strictly limited to one person working; most are small core teams of fewer than 10 people, relying on AI agents as digital employees to complete a full business loop. Self-employed individuals make money from their own time and physical effort, and much of the work cannot be replicated; OPC plays with "human capital," handing repetitive chores like organizing materials and debugging code to AI, leaving human energy for making judgments, finding pain points, and thinking of ideas. With the support of the community, OPC's advantages can be brought into fuller play. To use a simple analogy, the entire community is like a Transformer, and the dozens of resident OPCs are different building blocks. Each holds its own unique skills—some excel at writing vertical small models, some understand industry data processing. When a big project comes, no single entity needs to shoulder all the work alone; several blocks are selected as needed and assembled together to form a virtual team with divided labor. This perfectly explains what "OPC is not fighting alone" means.

Can hard tech projects land through the OPC model?

Hebei Qidong Brain-Computer Interface Technology Co., Ltd. is working on dexterous hand training. Put on a lightweight head-mounted device and stare at the computer screen. Text pops up on the screen in sequence: open, pinch, stop, V gesture, grip. Without moving hands, just by generating the corresponding thoughts in the mind, brainwave signals are collected and parsed by the head-mounted device, and the dexterous robotic hand beside it completes the entire set of actions—opening, pinching, making a V, and making a fist. Zhao Hao, general manager of Hebei Qidong Brain-Computer Interface Technology Co., Ltd., is training the dexterous hand, an external device of the brain-computer interface. Zhao Hao explained that brain-computer interfaces fall into three categories: invasive, which requires craniotomy to implant chips and is more popular abroad; semi-invasive minimally invasive; and non-invasive brain-computer interfaces, which are currently the focus of development in China—wearing a head-mounted device to collect brainwaves without surgery, with lower risk, suitable for the rehabilitation medical direction, and more suitable for large-scale use by ordinary patients. What Hebei Qidong Brain-Computer Interface Technology does is the external devices and industrial implementation of non-invasive brain-computer interfaces. Zhao Hao told reporters that the entire company can be divided into three parts: first, data collection, large model construction, and technology product R&D within the OPC community; second, building application scenarios in hospitals in Hebei; third, production. The three parts are organically combined, very close in distance, extremely flexible, truly forming a closed loop of industrial implementation. Zheng Ganghua did the math. In data collection, large model construction, and technology product R&D, a single person running AI consumes about 2 billion tokens per month. If purchased on external commercial platforms, the cost is 3,000 yuan per person per month. The team has three people running AI at high frequency. Relying on community-subsidized computing power, these three people directly save nearly 10,000 yuan in costs each month. Beyond computing power, the community also helped them connect with provincial top-tier hospitals to quickly obtain clinical testing scenarios; connected with science and technology authorities to assist in advancing Class II medical device qualification applications, seeking green channels, compressing the usual two-year certification cycle to about one year. In Zhao Hao's words, with an AI digital human team plus community services, the efficiency improvement is tangible: "We can quickly seize industry opportunities and greatly compress R&D cycles. A workload that originally took an engineer a year is completed in three months." Relying on the lightweight OPC model, hardcore technology can also land. Hebei Qidong Brain-Computer Interface Technology has provided a vivid practical sample.

Does being the smallest trial-and-error unit mean there is no risk?

Many people only see the glamorous side of OPC: simple registration, free time, no need to repeatedly spend money on physical experiments—it is the smallest trial-and-error unit. But they overlook the risks behind it: a one-person company must bear all the pressure of operations, finance and taxation, and debt alone. If personal and company property are mixed, the protection of limited liability can also be broken. AI tools also bring a series of new problems such as data security and output of false information. "For entrepreneurs, first weigh yourself—do you have real skills, can you solve real market needs, rather than following the trend and chasing hype," said Ge Zhi. "For community platforms, they cannot only provide nanny-style services like 'giving workstations and computing power,' but must also do a good job in scenario matching, resource brokering, and risk underwriting, truly helping entrepreneurs complete the business loop." There are no shortcuts in entrepreneurship. What OPC lowers are the thresholds for registration and manpower; the real threshold has shifted to people's cognition and industry accumulation. It gives ordinary people one more path, but this path still requires steady, down-to-earth progress.

Where is human irreplaceability reflected?

During the interview, Ge Zhi repeatedly emphasized one thing: AI can improve efficiency, but it cannot replace people's industry experience. "We need young technical talent, but for industrial projects, just knowing how to use AI tools is far from enough. We value the industry experience people have accumulated through frontline struggles. This solid industry cognition cannot be replaced by any amount of online training data." Ge Zhi spoke very practically: "The industry experience accumulated in the minds of frontline practitioners is the most precious wealth—this is something large models cannot obtain." For short dramas, AI can generate scripts in batches; but for real industries, the pitfalls in the industry, the real needs, and various real constraints in the implementation process cannot all be learned from online corpora. AI is good at summarizing, writing code, and organizing text, but it cannot understand real industry pain points. Zheng Ganghua shares the same view: "AI is only an R&D assistant, responsible for doing repetitive work and amplifying efficiency. For example, writing code for extensible functions and troubleshooting program bugs can be handed to DeepSeek; organizing massive medical records and experimental materials can be handed to Minimax. People set directions, make judgments, and output industry cognition. Decision-making power must remain in human hands. The most core brain-computer algorithms and medical judgments are all controlled by people." Ge Zhi admitted frankly that if ordinary people rush into industrial OPC on a whim, the probability of failure will be very high. Before entering, two things are unavoidable: first, truly understand the industry you are in and be clear about its pain points; second, thoroughly understand the characteristics of AI tools, and when necessary, develop native agents, rather than casually attaching AI to third-party systems to avoid data leaks. 2026 is called the first year of domestic OPC entrepreneurship in the industry. Ge Zhi predicts that in another year or two, the industry will face a major reshuffle. Teams that only follow the trend and join in the fun without a clear positioning will most likely be eliminated. Ge Zhi introduced that the community will continue to adhere to the industrial OPC route, continue to discover talent with frontline practical experience in all walks of life, combine people's industry experience with AI agents, and form teams to undertake the digital upgrading needs of Hebei's local hundred-billion and ten-billion-level industrial clusters.

Reporter's observation: In industrial OPC, capability and experience are the hard currency

When mentioning OPC, many people's first reaction is short videos and AI short dramas. Walking into the Qingyan Shuzhi OPC Community, the demonstration of a dexterous hand completing fist-clenching and pinching through brainwaves shows another possibility of OPC—industrial OPC. Industrial OPC is not a side hustle that ordinary people can enter with their eyes closed. It is more suitable for technical personnel and senior practitioners with frontline industry practical accumulation. AI is an efficiency tool that can write code and organize materials, but it cannot replace people's insight into industry pain points. Knowing only prompts without industry accumulation makes it difficult to solve real industry problems. Industry accumulation, continuous learning ability, and the ability to dispatch AI to complete scenario delivery are the real passports for industrial OPC. Doing industrial OPC well cannot be separated from the help of the community. The value of a high-quality OPC community has long gone beyond free workstations and subsidized computing power. More importantly, it is industrial scenario matching, resource connection, and risk escort. It helps small teams shoulder the complicated business registration, regulatory liaison, and external business affairs, allowing people who understand technology and industry to focus on their main business with peace of mind. Traffic tracks easily attract attention, but industrial OPC builds a long-term foundation. Orders come from real scenarios, value lands on industrial upgrading, and returns come from tangible technical services and achievement implementation. It may not quickly go viral, but as long as industries have upgrading needs, it has the soil to survive.