The National "Shrimp Farming Craze": From Lining Up to Install to Paying to Uninstall, What Signal Does It Send?

Source: Securities Times Network Author: Wu Shun Chen Yukang

“Did you raise a lobster today?” This seemingly common greeting in the aquaculture community has recently exploded in popularity, becoming a nationwide buzzword since 2026. The “lobster” here refers to an open-source AI agent called OpenClaw, affectionately nicknamed “Little Lobster” by netizens due to its red cartoon lobster icon. The process of deploying, training, and using this AI agent is humorously called “raising lobsters.”

Since the first official version was released over a month ago at the end of January, this nationwide craze driven by open-source technology has rapidly spread from the tech circle to the general public: offline “raising lobsters” experiences in cities like Beijing, Shanghai, Guangzhou, and Shenzhen; trending online topics across social media platforms; major companies launching “cloud lobster” services; local governments initiating “lobster-raising” competitions; and the AI concept in capital markets experiencing another surge. It seems a revolution in AI agent popularization is sweeping the country.

But behind this “lobster-raising” boom, questions remain: Is there a real demand for “raising lobsters,” or is it an irrational expectation amplified by marketing narratives? Does the high barrier to entry and learning curve mean it’s still far from being accessible to ordinary users? How can AI with extensive permissions ensure user safety? These issues will continue to test how far this “lobster-raising” trend can go.

“Raising Lobsters” Becomes a Policy Race: An Intense “Policy Competition”

OpenClaw can directly control computers and other devices to complete tasks, enabling a leap from conversational assistance to autonomous execution—“freeing hands”—making it a hot topic in tech and capital markets. On March 6, a long queue even formed outside Tencent’s headquarters: nearly a thousand developers and AI enthusiasts gathered at Tencent Tower, assisted by Tencent cloud engineers, to install OpenClaw on the cloud collectively, becoming “cloud lobster raisers.”

Zhang Cheng, Assistant Dean of Fudan University School of Management, Professor and Department Chair of Information Management and Business Intelligence, told Securities Times that “Lobster” not only processes content but can also flexibly call various tools and combine strategies like humans to complete tasks. How it achieves this black box is left to AI to experiment freely, allowing users to focus only on what they want, shielding them from technical complexities in automation.

As of March 10, in recent trading days, A-share market OpenClaw concept stocks experienced a surge, with several listed companies responding.

UCloud stated that their lightweight cloud hosting products equipped with OpenClaw images have not yet formed a scaled product system. Technological iteration and commercialization progress may fall short of expectations, with limited short-term impact on overall business performance. Autonomous AI frameworks like OpenClaw are still in early development stages, with uncertain future market potential, technical stability, and data security.

Previously, Nubia (ZTE) and ByteDance’s Doubao collaborated to launch Doubao AI phones, which became popular for features like “completing tasks in one sentence.” Regarding the impact of “lobsters” on AI phones, a ZTE terminal executive told Securities Times that they welcome the entry of “lobster phones” into the market to foster growth. However, compared to the various competitive advantages of “lobsters,” AI phones also have core strengths.

“‘Lobster’ has a high usage threshold, requiring local deployment, manual skill configuration, and is prone to errors and security vulnerabilities. Doubao AI phones are ready to use out of the box, eliminating complex debugging, and all key functions are user-driven in the final step, forming a last line of defense,” the executive explained.

Zhang Cheng believes that the high autonomy of “lobsters” comes at a cost. “The additional reasoning and programming test steps generated when AI tries different paths directly consume more tokens. Since more processes are handed over to AI, and AI itself can hallucinate or be fragile, this increases the risk of task loss of control,” he said. “‘Lobster’ essentially represents a new balance between user-friendliness, computational costs, and task risks.”

In this “raising lobsters” wave, local governments have also quickly followed suit, offering “real money” incentives to attract developers and enterprises, creating a fierce “policy race.”

For example, Longgang District in Shenzhen issued the “Ten Policies for Lobster,” offering up to 2 million yuan in subsidies; Wuxi High-tech Zone explicitly supports up to 5 million yuan per project.

Hu Bo, Honorary President of Zhejiang Investment and Financing Association and Founding President of Suzhou Industrial Park Development Promotion Association, told Securities Times that recent government policies supporting “raising lobsters” are a continuation and upgrade of previous OPC (one-person company) community support policies.

“Since last year, many regions have focused on building OPC communities, mostly supporting co-working spaces or incubators, without deep involvement in the technical foundation,” Hu said. “Now, with the rise of OpenClaw, these OPC communities have a technical base and empowerment tools, making the development logic of OPC models more solid, which has attracted government attention and support.”

High Learning Curve: “Raising Lobster” Guides Reach 800 Pages

As the “lobster-raising” craze continues, many ordinary users are researching how to raise this “lobster” well and have high expectations for OpenClaw’s capabilities. In fact, from the perspective of a large company’s cloud deployment of OpenClaw, the learning curve is extremely steep. For non-technical “newbie” users, even a simple computer term can cause hours of confusion.

Currently, many platforms have released guides and tutorials for OpenClaw. One such guide, totaling 800 pages, covers beginner basics, four core functions, advanced skills, and practical cases. It contains many technical terms, making it seem like a “bible” to users without programming backgrounds. However, this tutorial is only a superficial introduction; most skills still require users to explore and learn on their own.

What tasks OpenClaw can perform depends on its underlying “brain”—the large model. The smarter the model configured, the better OpenClaw performs. Its specific capabilities rely on skills—each skill can execute certain commands. The official skill marketplace ClawHub has nearly 20,000 skills, making it challenging for users to find suitable ones.

Even after finding the right skills, usage can be difficult. For example, if a user wants OpenClaw to automatically post on Xiaohongshu (Little Red Book), they need to log into Xiaohongshu on their local browser to get the Cookie, open developer tools with “F12,” refresh, find a request, copy the Cookie, and send it to OpenClaw. For ordinary users, locating and copying this Cookie is a significant challenge.

Senior AI investment expert and special researcher at Wangjing Society E-commerce Research Center Guo Tao said that, from an industry evolution perspective, the current popularity of “raising lobsters” is more of a phased technological application hotspot rather than a mature AI terminal form. Its core driver is the inclusive nature of open-source technology and users’ curiosity—OpenClaw, as an open-source project, lowers the barrier for ordinary users to access advanced AI agents. People can easily debug it to perform basic tasks like file organization and information retrieval, which quickly sparks social sharing. However, beneath the surface, its core technology remains experimental: functions are mainly on the PC side, limited to niche enthusiasts’ “geek” play, far from the public’s expectation of a “smart terminal.”

Guo Tao further pointed out that while open-source projects like “lobsters” provide valuable exploration for AI terminals, current agents lack stability, scene adaptation, and human-computer interaction standards for commercial use: command understanding accuracy is insufficient, complex task planning is limited, and over-reliance on text commands and lack of physical world perception hinder practical deployment. These flaws mean they are more suitable as experimental tools rather than consumer products at this stage.

Beware of Repeating Chaos: Accelerate Building Permission Governance Framework

While OpenClaw is gaining popularity, issues like accidental email deletion and privacy leaks are emerging. Many ads for paid “lobster” uninstallation flood social media, becoming another hot topic. The mixed reputation of “raising lobsters” has prompted warnings from various departments, injecting a dose of caution into the fervor.

The Ministry of Industry and Information Technology recently issued the “Six Do’s and Six Don’ts” advice on preventing security risks of OpenClaw (“lobster”) open-source AI agents. It highlights risks such as supply chain attacks and internal network infiltration in office scenarios; sensitive information leaks and hijacking risks in system operation; personal data theft and sensitive info leaks in personal assistant scenarios; and errors or account hijacking in financial transactions. Recommendations include using official latest versions, strictly controlling internet exposure, adhering to the principle of least privilege, cautious use of skill markets, preventing social engineering and browser hijacking, and establishing long-term protective mechanisms.

Local authorities also advocate rational use of OpenClaw. On March 11, Suzhou Artificial Intelligence Industry Association issued a statement urging the promotion of professional services for OpenClaw, provided by specialized organizations for secure deployment, capability training, and trustworthy delivery, so that AI agents can truly integrate into business processes as reliable productivity tools. Strictly implement security baseline configurations and follow the principle of least privilege.

The capital market responded swiftly. On March 11 and 12, several OpenClaw concept stocks in A-shares experienced sharp declines.

Guo Tao told Securities Times that, under current technology, the ambiguity of AI agent permissions could lead to excessive data collection, and the liquidity of open-source community code increases the risk of data leaks. If maliciously exploited, agents could become tools for privacy theft.

“More challenging is the difficulty in defining control and responsibility. When AI agents autonomously perform tasks and errors occur—such as incorrect transfers or mistaken messages—who bears responsibility—the user, the developer, or the device manufacturer? Currently, there are no technical standards for permission levels or legal regulations clarifying responsibilities,” Guo Tao said. “The industry should accelerate establishing permission governance frameworks based on the ‘minimum necessary’ principle. Regulations should also be improved to clearly define the ‘AI behavior responsibility chain.’”

Beyond technical vulnerabilities and security risks, the social trend of “raising lobsters” needs correction. As Hu Bo noted, “The current industry is overhyped and blindly following trends, which can mislead resource allocation and deviate from genuine development.”

He emphasized that, on the hype cycle, “safety must be prioritized.” Besides micro risks like data loss and privacy leaks, if the craze turns into disorderly social movements, it could lead to broader chaos—such as scams under the guise of “raising lobsters” or distributed computing power, or hype-driven projects promoting grand visions to attract investments. Similar phenomena have occurred in past bubbles like the metaverse and blockchain.

Of course, despite risks and controversies, industry experts generally believe that the widespread adoption of OpenClaw reflects a paradigm shift in AI: from “dialogue-based interaction” to “autonomous execution.” This trend and transformation could have profound long-term impacts on the economy and society.

Zhang Cheng said that the popularity of OpenClaw also indicates an accelerating trend of multi-AI agent collaboration, which may change the current emphasis on specialization. For example, AI could handle accounting, legal documents, and market analysis, allowing founders to focus more on core creativity and strategy, lowering entrepreneurial barriers. While division of labor won’t disappear immediately, it may become less fragmented, leading to more flexible enterprise structures.