Why is this round of "lobster craze" led by counties (cities, districts)?

Everyday Economic News Reporter: Liu Xuqiang    Editor: Yang Huan

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Image Source: Shutterstock 701027728

“Lobster” goes viral, official intervention follows.

On March 7, Shenzhen Longgang released the “Several Measures to Support the Development of OpenClaw & OPC (Draft for Comments)” (hereinafter referred to as the “Lobster Ten Rules”). Soon after, more news emerged—including policies supporting “lobster” in Wuxi High-tech Zone, Hefei High-tech Zone, Suzhou Changshu, Nanjing Qixia High-tech Zone, Hangzhou Xiaoshan District, and other regions.

Throughout the process, both the number of policies and subsidy amounts kept increasing. It’s clear that from the Greater Bay Area to the Yangtze River Delta, a race to develop the “lobster” industry has quickly ignited.

OpenClaw signifies a critical shift in artificial intelligence—from “dialogue” to “execution.” For cities, this will inevitably trigger a new wave of industrial transformation.

“In the era of multi-agent systems, whoever first completes the closed loop will secure their position,” said Zhao Bingbing, Director of the Artificial Intelligence (Robotics) Department in Longgang District, Shenzhen, in an interview with City Evolution. Cities that deploy “lobster” early are expected to take the lead in industrial change and become pioneers of the new paradigm.

With OpenClaw gaining rapid popularity, related concepts like OPC (One Person Company) are also drawing renewed attention. From OpenClaw to OPC, major cities like Shenzhen, Shanghai, Beijing, and Hangzhou are vying to be the first to implement large-scale deployment.

Another noteworthy detail is that this round of industry deployment is mainly led by counties (cities, districts). What new development trends might this reveal?

Race for the Trend

From the Greater Bay Area to the Yangtze River Delta, “lobster” has become a new industry hotspot that cities are competing to develop.

Image Source: OpenClaw Official Website

First, Shenzhen Longgang launched the “Lobster Ten Rules,” offering subsidies and computing power support, with a maximum subsidy of 4 million yuan, aiming to create a “zero-cost startup” environment for AI entrepreneurs.

After Shenzhen’s initial move, policy support among other cities has visibly intensified: Wuxi High-tech Zone, Suzhou Changshu, Hefei High-tech Zone, Nanjing Qixia High-tech Zone, Hangzhou Xiaoshan District, and other Yangtze River Delta cities have announced plans to develop “lobster,” with policies becoming more detailed and subsidy caps gradually rising.

From broad policy coverage to continuous strengthening of support, it’s evident that local governments are fiercely competing on this new track, eager to secure their positions.

To understand this policy race, one must first grasp the impact of OpenClaw on the entire AI industry—its disruptive power lies in breaking down technical barriers and pushing the industry toward a new stage of “inclusive and practical” AI.

Shen Hao, Chief Engineer of the Shanghai Artificial Intelligence Institute, pointed out that as a phenomenon-level open-source AI agent, OpenClaw lowers the public’s understanding threshold of AI, making society directly perceive the tangible value of AI carriers, and promoting technology from “industry giants’ exclusive domain” to “accessible to all.”

This inclusive revolution is fostering new industry forms, not only accelerating the rise of “AI+” sectors like virtual hosts and smart peripherals but also pushing AI technology toward more realistic and interactive capabilities.

More importantly, OpenClaw has pioneered a new technological paradigm of multi-AI collaborative invocation.

Economist and member of the Ministry of Industry and Information Technology’s Information and Communications Economic Expert Committee, Pan Helin, emphasized that OpenClaw opens a new mode of multi-AI collaboration—by invoking other AI tools, cloud computing, software, and search engines to complete complex tasks for users. Over time, such applications will mature and become the trend.

Zeng Gang, Dean of the Urban Development Research Institute at East China Normal University, noted that the government work report in 2026 first introduced the concept of “intelligent agents,” emphasizing “cultivating new forms of intelligent economy” and “supporting the development of entrepreneurial models suited to the AI era.” The continuous issuance of policies supporting OpenClaw reflects, to some extent, a response to national strategic deployment.

“The open-source nature and cross-platform capabilities of OpenClaw make it a ‘new operating system’ connecting cloud computing and end-user hardware, creating opportunities to ‘rebuild’ all hardware,” Zeng Gang further explained. Major cities’ efforts to deploy OpenClaw aim to seize strategic high ground in “AI+ manufacturing” and “smart terminals.”

Many share the view that the emergence of OpenClaw will be another “DeepSeek moment” in city AI industry planning. In a sense, its impact at the application and industry level could be even more profound.

“As the government is willing to promote technological progress, especially in building a new form of smart economy, to better play its role and accompany everyone in trial and error,” said Zhao Bingbing. The rapid rollout of support policies by cities signals to AI entrepreneurs that “once here, you can stay and develop well.”

However, attention must also be paid to potential risks. Pan Helin pointed out that most “lobsters” are locally deployed, and security risks are the most feasible response to the “lobster craze.” Additionally, encouraging large AI enterprises to develop secure, OpenClaw-like products through open-source communities and continuously enriching their functionalities is essential.

OpenClaw is still in its early stages; “raising lobsters” requires caution, and safety cannot be overlooked. Shen Hao also mentioned the need to address risks related to agents’ information security and to establish normative rules promptly.

Regional Ecosystems

Local “lobster” policies often coincide with the emergence of OPC support.

This is understandable—starting from open-source core capabilities to enabling individuals to start their own businesses, there is a clear pathway driven by local governments racing to develop AI, aiming to lower barriers and incubate the next unicorn.

Currently, subsidies are a major attraction for AI entrepreneurs interested in “raising lobsters.” Although OpenClaw is free and open-source, the process of “raising lobsters” consumes a large amount of tokens, which users must pay for themselves. Media reports indicate some users spend an average of 30,000 yuan per month on token consumption.

Government financial backing can help startups get through the “token tuition” phase but cannot build long-term cost advantages. Therefore, for local governments, policy support is not just about initial subsidies but also about fostering sustainable ecosystems.

At present, leading Chinese cities are actively developing OPC ecosystems. Beijing, leveraging Zhongguancun’s AI Beiwang Community, has launched an AI OPC service plan, coordinating capital, universities, and industry resources to form the country’s first systematic, full-cycle OPC cultivation system.

Shenzhen, through policy innovation, issued the “Action Plan for Building an AI OPC Startup Ecosystem (2026–2027),” aiming to establish over 10 OPC communities and cultivate more than a thousand high-growth enterprises by 2027.

Similar policies are widespread.

The OPC potential of various regions can be ranked: in February this year, Tsinghua University’s School of Journalism and Communication’s New Media Research Center and others released the “2026 China OPC Startup City Development Index and Rankings,” with Suzhou and Shanghai leading the first tier, Shenzhen, Beijing, Wenzhou, and Nanjing in the second, and Hangzhou, Wuxi, Guangzhou, and Fuzhou in the third.

Image Source: China Association of Small and Medium Enterprises, Artificial Intelligence Special Committee

Beyond rankings, the specific development paths of cities are more noteworthy. Zeng Gang believes that among China’s top cities, Shenzhen and Shanghai show the strongest potential for large-scale OPC deployment.

Shenzhen’s approach is “vertical industry penetration”: leveraging its hardware supply chain advantages, Shenzhen can quickly facilitate large-scale diffusion of OpenClaw from digital to physical worlds. Whether it’s embodied intelligent robots, smart wearables, or industrial inspection systems, Shenzhen can rapidly complete the “technology-product-market” closed loop.

Shanghai’s path is “horizontal ecosystem replication”: Zeng Gang points out that the exploration of OPC super-individual communities in Yangpu District’s Fuxingdao demonstrates that Shanghai’s “university + large enterprise” industry-university-research collaboration, combined with agile government services, has created a conducive environment for innovation. Once this model proves successful, it can be quickly replicated in other parts of Shanghai and the Yangtze River Delta, forming multiple high-density innovation nodes.

As Pan Helin said, the development of OpenClaw in various regions should rely more on existing advantages. For example, Shenzhen’s cloud computing capacity, Hangzhou’s Alibaba and “Six Little Dragons” enterprise clusters are core capabilities supporting large-scale deployment.

At the same time, common bottlenecks in OPC development are gradually emerging.

Ruo Weihong, Vice Chairman of the Standing Committee of Hangzhou Municipal People’s Congress, recently told media that China’s OPC industry still faces issues such as rigid traditional institutional frameworks, isolated entrepreneurial ecosystems, and insufficient innovation support. This means that while many regions are issuing special policies, they must also improve policy precision and coverage.

A key breakthrough is opening government AI application scenarios and public data resources. Ruo Weihong suggested that, under the premise of ensuring security and privacy, public data and scientific research data should be opened to OPCs in a graded and classified manner.

Key Platforms

A clear trend in the development of new industries is that increasingly more industry policies are led by county (district, city) governments.

For example, in the “Lobster Regulations” issued by various regions, districts like Shenzhen Longgang, Wuxi High-tech Zone, Hefei High-tech Zone, Suzhou Changshu, and county-level cities are the main policy issuers.

Shen Hao pointed out that compared to provincial and municipal governments, district-level governments are closer to enterprise needs, can respond quickly to technological iterations, and have faster policy response speeds.

Taking Shenzhen Longgang’s “Lobster Ten Rules” as an example, Zhao Bingbing explained that Longgang’s ability to pioneer such policies is mainly due to establishing a dedicated agency that consolidates industry-related functions previously scattered across departments.

As early as 2025, Longgang established the nation’s first government-affiliated agency in the AI and robotics field—the Human-Machine Department. Its official role is clear: overseeing industry planning, ecosystem building, enterprise services, scenario promotion, and safety management, specifically supporting AI and robotics industries.

For local AI companies, the Human-Machine Department is the “first point of contact” for government services. For policy formulation, this flat organizational structure also reduces the cumbersome process of multi-department approval, greatly improving decision-making and execution efficiency.

Therefore, even before OpenClaw became popular, the Human-Machine Department had already led several “pre-embedding” policies, strategically positioning resources and laying groundwork for rapid response to industry hotspots.

“OpenClaw exploded in early March, and Longgang District released a dedicated policy on March 7. Such speed can only be achieved by grassroots departments familiar with the industry,” Zeng Gang said. This “Longgang speed” highlights the unique advantage of grassroots government-led industry policies—shifting from traditional “step-by-step” approaches to more agile “responsive” strategies.

Zeng Gang further stated that these recent “lobster” policies indicate that China’s industry policy-making is moving from top-down “macro design” to more flexible, locally tailored “bottom-up” approaches at district or bureau levels.

He believes this benefits industry policy by shifting from “broad, indiscriminate support” to “targeted, precise support.” Historically, most industry policies were issued by national or provincial governments, but future policies will increasingly come from local governments, better aligning with enterprise and societal needs.

Additionally, the logic of industry policies is changing—from “competing for land and incentives” to “building ecosystems and fostering innovation.” The core of the “Lobster Regulations” is no longer land or tax cuts but creating ecosystems around data, computing power, scenarios, and talent—responding to local economic development needs for new drivers.

Furthermore, district governments often serve as “test beds” for policy innovation. Small-scale experiments can accumulate experience for broader implementation. Many regions’ “lobster” policies are currently in consultation, reflecting cautious exploration.

Ultimately, the development and application of “lobsters” and other intelligent agents are not overnight achievements, nor are they mature industries. Large-scale productivity gains require long-term planning. How to ensure that funding subsidies truly encourage innovation depends on continuous adjustments and clearer, more rational policy frameworks.