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 is a greeting in the aquaculture circle, which has recently exploded in popularity and become a nationwide buzzword since 2026. The “shrimp” 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 agent is also playfully called “raising shrimp.”

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 community to the general public: offline “raising shrimp” experiences in cities like Beijing, Shanghai, Guangzhou, and Shenzhen have surged; related online topics flood social media; major companies have launched “cloud raising” services; local governments have initiated “raising shrimp” competitions; the AI concept in capital markets has reignited, and a revolution in AI agent popularization seems to be sweeping the country.

But behind this “raising shrimp” boom, is there a real demand 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 ordinary users? How can AI with extensive permissions ensure user safety? These questions will continue to test how far this “raising shrimp” trend can go.

Raising Lobsters: A Fierce “Policy Race”

OpenClaw, an AI tool capable of directly controlling computers and devices to complete tasks—ranging from conversational assistance to autonomous execution—has become a hot topic for both tech circles 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 in the cloud, collectively becoming “cloud shrimp 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 performance. Autonomous AI agent 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 “Lobster” on AI phones, a ZTE terminal executive told Securities Times that they welcome the entry of “Lobster phones” into the market to jointly cultivate it. However, compared to the various competitive advantages of “Lobster,” 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 said.

Zhang Cheng believes that the high autonomy of “Lobster” comes at a cost. “The additional reasoning and programming test steps generated when AI tries different paths directly increase token consumption. 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 explained. “‘Lobster’ essentially represents a new balance between user-friendliness, computational costs, and task risks.”

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

For example, Longgang District in Shenzhen issued the “Lobster Ten Policies,” 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” can be seen as an extension 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 enabling tools, making the development logic more solid, which has attracted government attention and support.”

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

As the “raising shrimp” craze continues, many ordinary users are researching how to raise this “shrimp” well and have high expectations for OpenClaw’s capabilities. In fact, from the OpenClaw deployed on a major company’s cloud observed by Securities Times, the learning curve is extremely steep. For non-technical “newbies,” even a simple computer term can cause hours of confusion.

Currently, many platforms have released guides and tutorials for OpenClaw. One such guide, with nearly 800 pages, covers beginner basics, four core functions, advanced skills, and practical cases. It contains many technical terms, which can seem like “a foreign language” to users without programming backgrounds. Moreover, this 800-page 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 by the user, the better OpenClaw performs. Its specific capabilities depend on its skills—each skill can execute certain commands. Currently, 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, user operation can be difficult. For example, if a user wants to automate posting 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 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 perform basic tasks like file organization and information retrieval through simple debugging, which quickly sparks social sharing. However, beneath the hype, its core technology remains experimental: functions are concentrated on PC command execution, limited to niche enthusiasts’ “geeky” play, far from the public’s expectation of a “smart terminal.”

Guo Tao further pointed out that while “Lobster” open-source projects 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, planning for complex tasks is limited, and over-reliance on text commands and lack of physical-world perception and interaction restrict their application. These flaws mean they are more suitable for technical experiments at this stage rather than mass-market products.

Beware of Repeating Chaos: Accelerate Building Permission Governance Framework

While OpenClaw is gaining popularity, issues like accidental email deletion and privacy leaks have emerged. Many paid ads for uninstalling “Lobster” appear on 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, highlighting risks such as supply chain attacks, internal network infiltration, sensitive data leaks, hijacking, and account takeovers in different scenarios. Recommendations include using the latest official 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, the 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. They emphasize strict security configuration baselines and adherence to 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, these agents could become tools for privacy theft.

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

Beyond technical vulnerabilities and security risks, the social trend of “raising lobsters” needs correction. As the Suzhou AI Industry Association noted, “The current industry is overhyped and follows blindly, which can mislead resource allocation and deviate from genuine development.”

Hu Bo believes that in the face of such a trend, safety must be prioritized. Besides micro risks like data loss and privacy leaks, if the “raising lobsters” craze evolves 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 schemes promoting AI agents and ecosystems to attract investments. Similar phenomena have occurred in past bubbles like the metaverse and blockchain.

Of course, despite risks and controversies, industry experts generally agree that the popularization 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, thus lowering entrepreneurial barriers. While division of labor won’t disappear immediately, it may become less fragmented, leading to greater organizational flexibility.