OpenClaw's Father Amazed by China's Speed: Big Firms Collectively Enter New Battlefield of Using AI to Mass - Produce "One

In less than a year, the revenue exceeded hundreds of thousands.

“In less than a year, I've made hundreds of thousands of dollars and more.” said Rui Meng, a practitioner of the One - Person Company (OPC).

In the past, this was almost impossible. Developing an internet product usually required the cooperation of a complete team including product, engineering, design, and operations. However, with the development of AI programming tools and Agents, this rule is being rewritten. The prediction of “one person, a billion - dollar company” put forward by Sam Altman in 2023 is gradually becoming a reality.

Although the single - person unicorn has not truly emerged, “one - person companies” have emerged in large numbers. Especially after OpenAI swept across the country, this AI - driven reconstruction of the entrepreneurial threshold has obviously taken another big step forward.

Many people's starting points in this field are very ordinary. For example, Tata was originally a full - time stay - at - home designer. She initially contacted AI just to find a new source of income, and now she is doing content entrepreneurship through AI tools. There is also Wang Shu, a former product manager who recently left an internet company. Now he is developing small applications to verify demand and trying a more lightweight way of entrepreneurship. There is also Wu Ruimeng, a technical practitioner with a CTO background, who provides customized solutions for enterprises through AI tools and thus earns a considerable income.

For the first time, even technology novices can independently complete a full product cycle. For example, Tata only really started contacting AI in the past one or two years, but now she has begun to try to shift from the traditional workplace to a more independent entrepreneurial form.

According to the data provided by Miaoda, about 36% of users are already developing applications with monetization capabilities, which is a relatively high proportion. This includes not only one - person companies but also small teams, enterprises, and individual developers doing side jobs. In terms of user demands, 59% of people want to implement their ideas, 49% hope to make money or explore side jobs, and 35% use it to improve work efficiency. In contrast, the proportion of people who simply experience AI (17%) or use it for personal display (16%) is significantly smaller.

This means that a clear trend is emerging: most users no longer regard the AI platform as a tool to try new technologies, but start to use it to truly realize ideas and create income.

The Development Model of One - Person Companies

Choose the Easiest - to - Use Tools

In the one - person company model, AI tools are not only development software but also the infrastructure that determines whether a project can operate continuously. From the practical experience of many one - person company founders, the requirements for AI development tools are not complicated: low threshold, fast feedback, good collaboration, and stable platform.

Many one - person company founders do not have a technical background. They neither have the time nor the need to deeply learn programming languages. Therefore, the tools must be able to complete application development through natural language or simple configuration, enabling non - technical personnel to quickly build product prototypes. Only when the technical threshold is low enough can individual entrepreneurs focus their energy on product thinking and business models instead of being dragged down by complex technical details.

In the product exploration process of one - person companies, prototypes are often the most important communication medium. Many people's approach is that once they discover potential demand, they first use AI development tools to quickly build a usable prototype, then directly send the link to target users for communication and testing, listen to their feedback on functions and user experience, and at the same time verify whether they are willing to pay for this product.

Therefore, for one - person companies, the speed of trial - and - error is far more important than the complexity of functions. After the product is launched, it is also necessary to continuously iterate small versions to improve functions, which means that the platform must support frequent modifications and continuous optimization rather than one - time development.

To some extent, this is not fundamentally different from the development logic of traditional internet products. In the past, teams would first create a test version, then invite users to experience it and continuously optimize it. The difference lies in the change in efficiency. According to Wang Shu's experience, he can have an idea in the morning and complete the prototype and hand it over to users for testing in the afternoon, greatly shortening the cycle from idea to verification and making it quicker to determine whether the product is worth further investment.

The stability and long - term development prospects of the platform are also crucial. One - person companies often do not have the resources to repeatedly migrate the technology stack. Once the selected platform suddenly stops maintenance or changes its product route, the previous investment may all be in vain. Therefore, many entrepreneurs prefer platforms backed by large companies, believing that products of large companies are more certain in terms of resource investment and long - term operation.

For example, in actual production, AI development platforms usually rely on ecological components such as plugins and model interfaces. If these components are frequently taken off the shelves or there are policy risks, it will directly affect the operation of existing applications. Therefore, a stable and sustainable plugin ecosystem has also become an important consideration when one - person companies choose tools.

Communication Skills are Crucial

However, what really determines whether an AI project can succeed is often not the tools themselves, but how people use these tools.

In practice, the application of founders and AI tools is more like a continuous communication process: constantly putting forward requirements, verifying results, and then adjusting the plan. Compared with putting forward complex requirements at once, advancing one function module at a time is often more effective. Therefore, good tools need to support this dialog - style, modular development model, allowing individual developers to gradually build products.

Wang Shu's experience is that choosing a track is the first step, and you need to figure out whether this application is for monetization or just for fun. If you want to monetize, you need to know who the target users are, what the usage scenarios are, and then consider how to solve their problems.

Next, it is a process of repeated communication with AI: determining how to develop the product, how to build the structure, and how to implement it. It is necessary to meet user needs without over - designing, otherwise, it will be difficult for AI tools to develop. This requires personal judgment to decide which functions to remove and which to add.

Wang Shu emphasizes that communication skills are crucial. His experience is to tell AI only one function point at a time, let it fully implement and prove itself, and then check the effect. If you put forward too many requirements at once, although AI says it has achieved them, it may not be the case in reality. After changing to stating one problem at a time, the situation will be much better.

During this period, developers need to be patient. Although AI tools can quickly produce the first version, adding functions and making revisions later require continuous communication with AI. For example, Wang Shu's MBA writing correction tool, which sounds simple, has gone through more than 40 small iterations before becoming a usable product.

When Wu Ruimeng works on projects, he is used to running three versions simultaneously: the first focuses on UI design; the second starts from the user's perspective and revolves around requirements; the third combines the ideas of the first two from a technical perspective. He will only start the fourth version after all three reach the demo version.

In Wu Ruimeng's view, the greatest advantage of AI is its creative ability. “I'm neither a product manager nor good at marketing. I'm not good at skills like traffic and operations. But AI can help me make up for these deficiencies, allowing parallel exploration. I'll do the integration and judgment in the end.” He said, “Sometimes, the result may not fully meet the initial expectations, but overall, it's often better than working alone. This is the value of AI assistance.”

“One - Person Company” Doesn't Really Mean Only One Person

In many people's imagination, a “one - person company” means that all things are done by one person. However, from practice, this is actually a misunderstanding.

The core of a one - person company is not “doing everything by oneself” but compressing the organization to the minimum while making the business run the fastest. In this model, outsourcing is not a supplement but an integral part of the entire company structure.

Tata emphasizes that what entrepreneurs really need to do is to maximize their core capabilities. For example, product design, user insight, content creation, or professional capabilities in a certain vertical field. These links that determine the product value must be in their own hands. And those standardized and process - based tasks, such as financial accounting and legal processes, can be completely handed over to mature outsourcing teams. These related services are already highly developed. Entrepreneurs only need to control key nodes to maintain the operation of the enterprise at a very low cost.

More importantly, “super individuals” in different fields can be “outsourcing” for each other, and when combined, they form a complete team. One person is responsible for the product, one for design, and one for content. Together, they form a lightweight but complete team. Compared with traditional companies, this kind of cooperation relationship is more flexible and easier to adjust according to project needs at any time.

In Wang Shu's view, the minimum - cost model of a one - person company is: one or two core personnel, and the rest rely on outsourcing.

Some People Make Money, but It's Far from a Gold Rush

In the business model of one - person companies, running through the path is often not complicated, but it is far from as common as the outside world imagines. From current practice, the commercialization of one - person companies shows several obvious characteristics: following technological trends closely, serving long - tail demands, and having an obvious head effect.

Many successful one - person company projects are closely related to the current technological wave. For individual entrepreneurs, going with the trend is often more realistic than innovating against the trend.

Most of Wu Ruimeng's projects are related to AI because AI is currently popular. He said, “People should follow the trend to access the latest information and make up for the information gap. You can't still focus on SEO optimization now. Although SEO is not bad, GPT has already emerged, and old things will eventually be replaced by new ones.”

Currently, Wu Ruimeng mainly serves small and medium - sized enterprises with customized needs. For example, small studios specializing in car modification or some Taobao merchants. These people have needs but it's not worth (or they don't have the money) to hire a complete development team. Based on platforms like Miaoda, Wu Ruimeng can very quickly help them build a solution that meets specific scenario needs.

The thing itself is not complicated. What really makes the difference are some “soft skills”: Can you find these small and medium - sized enterprises and actively serve them? Do these small and medium - sized enterprises themselves realize that they can solve problems in a lower - cost and faster way with AI coding? Once the customer's perception changes, they will naturally look for people who can provide such solutions.

The main commercialization space of one - person companies often comes from small and medium - sized enterprises and the long - tail demand market. The scale of such demands is not large individually, but the quantity is huge, which is just suitable for the lightweight structure of one - person companies.

One of the reasons why Zhu Guangxiang, the product manager of Baidu Miaoda, is optimistic about the long - term development of one - person companies is that they can effectively solve long - tail scenario demands.

He analyzed that demands can be divided into two categories: high - frequency scenario demands and long - tail scenario demands. High - frequency scenarios such as social and information flow, which everyone has a need for, like WeChat and Douyin, are definitely developed by large companies. Because serving a large user group requires ensuring an excellent experience, which requires a very high R & D cost and is not suitable for one - person companies. Now, large companies have been operating for 25 years, and this has become a stock market. At this time, having too many employees is actually a negative competitive factor.

On the other hand, small scenarios like building a course - selection system for middle schools are particularly suitable for one - person companies. Although the scenarios are small, the quantity is extremely large and the cost is low.

“Previously, these scenarios were not released because the IT companies that controlled R & D resources had a large number of employees and programmers were expensive. It was not cost - effective to take on such small jobs, so they basically remained untouched.” Zhu Guangxiang further said, “Now with the arrival of AI Coding, the threshold has been greatly reduced, and these small demands are starting to be released. As long as there are demands, there will be space for one - person companies. It will reach the saturation period only when the demands in all industries are met and the digital construction has generally improved. Now it's still far from that.”

However, from the overall income of founders at present, the monetization ability of one - person companies shows an obvious “pyramid structure”. Taking the Miaoda ecosystem as an example, there are indeed individual developers with an annual income of hundreds of thousands of yuan, but the proportion of such people is not high, usually only in the single - digit range. The vast majority of participants are still in the stage of continuous trial and exploration, and those who can make continuous profits are concentrated among a few top creators.

In other words, a one - person company is not an easy way to get rich.

An overseas developer spent $47,000 and 18 months following the trend to build an “AI startup”, but it ended in failure. His advice is: Only when you have very deep professional accumulation in a specific industry, can access the decision - makers in this industry, and the problem you target causes the company to lose more than $100,000 a year is it worth doing.

It can be seen that in this model, being able to seize the trend, find real demands, and establish a stable user relationship is often more important than technology itself.

In addition, from the perspective of financing, one - person companies have not received capital support commensurate with their number. Data from Carta Insights and Solo Founders shows that in the startups established in 2024, one - person companies accounted for 30%, but in the priced equity financing rounds of that year, such companies only received 14.7% of the funds. This indicates that although the capital market has begun to accept the one - person company founder model, overall, it still tends to invest more funds in multi - founder teams.

When Creativity is No Longer Scarce, Where is the Moat of One - Person Companies?

When the technical threshold is greatly reduced by AI, it is difficult for creativity itself to form a long - term barrier. Once an idea appears, it will soon be imitated. Therefore, in this environment, the competitiveness of one - person companies comes more from speed, personal resources, and structural efficiency.

With the support of AI tools, the cycle from idea to prototype and then to product launch has been greatly compressed. When a creative idea appears, whoever can develop it faster and verify the market has a better chance to take the lead.

On the other hand, the execution speed of an individual is very different from that of a team, but it is faster and more flexible. Wu Ruimeng developed a similar product before the Coze workflow came out, but he didn't commercialize it. As soon as Coze appeared, he abandoned this project and invested in other projects.

In the fierce competition, personal brand and resource accumulation are particularly important. “If your brand, influence, and resources are not enough, the threshold will be easily flattened by others, and they can copy you without any cost.” Wu Ruimeng said directly.

In an era when creativity is easily replicated, personal influence has become an important moat. When entrepreneurs have a certain network, resources, and brand recognition in a certain field, new products are more likely to be noticed by the market and gain users and cooperation opportunities. On the contrary, even if an excellent product is developed, it may be buried in the market and eventually be replicated and magnified by later - comers. In other words, in addition to product capabilities, personal brand, social network, and resource integration capabilities are becoming important factors for the success of one - person companies.

In addition, compared with many large - scale companies, although one - person companies are small in size, they have extremely low costs and extremely short decision - making chains, and often have more advantages in terms of efficiency and profit margins. Wu Ruimeng mentioned that in reality, there are already many digital nomads or independent developers who can earn millions of yuan a year by operating products through AI tools, and their profits even exceed those of many small and medium - sized enterprises.

From a personal perspective, not everyone is suitable for entering the one - person company field. People who can really make a one - person company successful often have several common characteristics: clear professional accumulation, willingness to continuously learn, and the ability to actively collaborate with AI.

In Wu Ruimeng's view, the most suitable people for one - person companies are those with long - term accumulation in a certain vertical field. Opportunities in the AI era are more likely to appear in niche scenarios rather than in general - field competition. Everyone can be regarded as a “vertical model” in their own industry: designers understand design, technical personnel understand development, operators understand traffic, and e - commerce practitioners understand transaction links. These experiences are the cognitive advantages accumulated through years of work and are the most difficult part to be replicated.

“Deeply cultivate in your own profession and use AI to amplify your advantages instead of using it to make up for your weaknesses. Making fewer mistakes means being faster.” Wu Ruimeng said.

At the same time, one - person companies also place higher requirements on personal initiative and learning ability. AI tools are updated extremely fast, and new capabilities and products appear almost every one or two weeks. If a person stops learning, they will easily be left behind by new tools and new ways of playing. Therefore, those who can continuously learn and experiment with new tools are more likely to find opportunities in this model.

Wu Ruimeng summarized