The hype surrounding OpenClaw has finally begun to subside.
At the Morgan Stanley Technology Conference, NVIDIA CEO Jensen Huang heaped praise upon OpenClaw, declaring: “OpenClaw may well be the most significant software release in history. It surpassed—in just three weeks—the level of ubiquity that took Linux some 30 years to achieve, becoming the most downloaded open-source software globally.”
For he could finally explain why tech giants were shelling out massive sums to purchase his computing cards: “Lobster” would consume colossal quantities of tokens.
Huang excitedly predicted that OpenClaw would drive an exponential surge in token consumption; the resulting supply-demand imbalance for computing power would create a “computational vacuum,” thereby compelling a continuous cycle of hardware architectural upgrades.
OpenClaw’s defining feature is its ability to bridge the gap between large language models and local operating systems, enabling automated, cross-application execution and feedback loops. As described by its creator, Steinberger: “It is a framework that allows AI to truly get to work on your computer.”
This unique selling point sent internet giants into a frenzy of excitement. After all, not everyone is a tech geek capable of handling local deployments on their own; by offering cloud-based subscription services, these companies could not only amortize their massive upfront capital expenditures on AI infrastructure but also spin a compelling narrative of “AI productivity” for the capital markets.
Furthermore, against the backdrop of widespread “AI anxiety,” it seemed no one wanted to be left behind. Consequently—around the time of the Lunar New Year in the Year of the Horse—fueled by the high-profile endorsements of tech bloggers, OpenClaw became a scorching hot topic across the Chinese internet.
It must be admitted that when it comes to capturing internet traffic, these “course-selling gurus” certainly have their tactics down to a science. Open-source accessibility and one-click deployment capabilities were repackaged as “free to use” and offering “zero barriers to entry.” Meanwhile, the underlying technical principles of these AI agents were glossed over, and the necessity for high-level system permissions was conveniently downplayed; instead, the focus was placed almost exclusively on “high commercial returns” and the promise of an “AI dividend.” This highly targeted rhetoric stoked the AI-related anxieties of ordinary users—and allowed these influencers to reap a hefty harvest of “tuition fees.”
Yet, as is the case with all AI fads: if you are slow to jump on the bandwagon, you might as well not bother at all. In less than a month, hardly any ordinary people were talking about “Lobster” anymore.
The simple truth is: ordinary people have absolutely no need for such sophisticated gadgetry.
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It was Tencent that truly ignited the OpenClaw craze(Chinese call it Shrimp Farming) within China.
Tencent founder Pony Ma personally “promoted” the tool on his WeChat Moments; subsequently, companies such as Tencent, Alibaba, ByteDance, and Xiaomi swiftly launched products and services compatible with OpenClaw within a short timeframe. Across the country, high-profile events were held offering free assistance to users looking to deploy OpenClaw. Of course, this also served as an opportunity to deeply integrate users into their own respective ecosystems, with the ultimate goal of driving paid conversions.
Bolstered by high-frequency coverage from major media outlets, OpenClaw rapidly broke out of its niche within just one week. According to official data from Tencent Cloud, the number of “shrimp farmers” (users) on the cloud platform has now surpassed 100,000.
Amidst this continuously escalating hype, Tencent seized the momentum to launch SkillHub—a localized mirror platform for OpenClaw. By synchronizing a vast array of official “skill” resources from the overseas ClawHub platform, Tencent drew the ire of Steinberger, OpenClaw’s creator. He took to social media to complain that Tencent’s actions were placing an excessive load on the project’s servers, noting that OpenClaw itself was receiving no reciprocal support or benefit from this sudden surge in popularity.
However, Tencent quickly leveraged its “financial might” to resolve the issue.
Tencent explained that the vast majority of SkillHub’s traffic load is independently borne by Tencent Cloud, refuting the accusation that it was merely “taking without contributing.” Furthermore, Tencent officially joined the OpenClaw community as a corporate sponsor, providing substantial support to the project through funding, computing power, and ecosystem resources. Steinberger signaled his reconciliation by describing the resolution as “a beautiful redemption.”
Moreover, Tencent revealed plans to soon launch a comprehensive, multi-scenario product suite—encompassing “self-developed shrimp,” “local shrimp,” and “cloud-based shrimp” solutions. Concurrently, the company is constructing secure, isolated “shrimp tanks” (environments) to enable deep integration between these “shrimp” agents and Tencent’s existing core social and office tools, such as WeChat Work, QQ, and Tencent Meeting.
Fundamentally, OpenClaw was designed as a tool for tech enthusiasts and “geeks.” Its deployment involves specialized technical steps—such as environment configuration and API key management—and its usage is not free; instead, costs accumulate based on a “token-in plus token-out” billing model, making both its implicit and explicit costs quite substantial.
Consequently, while OpenClaw garnered some public attention in overseas markets, its circulation remained largely confined to tech communities like GitHub. NVIDIA CEO Jensen Huang’s strong endorsement of the project was similarly rooted in the belief that the successful real-world application of AI agents validates the necessity of building large-scale AI infrastructure—thereby creating a more predictable and reliable demand for NVIDIA’s products.
In contrast, Tencent’s frantic rush to transform “shrimp farming” into a mass-market activity clearly stems from a very different strategic mindset.
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From a logical standpoint, the rapid progress of this “shrimp-farming” initiative—nurturing a new venture from scratch—clearly indicates that this was no unprepared battle. Even in an AI era where the landscape shifts daily, such a comprehensive product line could never be the result of a spur-of-the-moment decision.
OpenClaw appears less as a standalone project and more as a vehicle—one that Tencent happened to discover at just the right moment. Its open-source nature allows Tencent to naturally leverage its architecture as a reference point for developing its own “counterpart” products; moreover, the practical application of the “AI Agent” concept offers Tencent a strategic opportunity to overtake competitors by “cutting corners” in the race for AI dominance.
In January, during an employee town hall meeting, Pony Ma (Ma Huateng) made a rare public admission: Tencent had, in fact, been “slow to act” in the AI sector.
For a considerable period, Tencent’s strategic focus remained firmly fixed on mature “cash cow” businesses—primarily social networking and gaming—while its strategic prioritization of large AI models and AI agents remained relatively conservative. This cautious, “take-it-slow” mindset at the executive level filtered down to the operational ranks as a stance of “wait-and-see” and excessive prudence.
AI R&D efforts were fragmented across multiple business groups; data silos existed between departments, models lacked standardization, and resources were severely squandered. It was not until late 2024 that Tencent’s AI products—”Yuanbao” and the “Hunyuan” large language model—were finally transferred from the Technology Engineering Group to the Cloud and Smart Industries Group, thereby officially initiating their productization phase. By that time, rival products—such as ByteDance’s “Doubao” and Alibaba’s “Qwen”—had already seized critical market windows.
The WeChat “super-ecosystem” itself had also become a “sweet yoke”.
Out of concern for crossing user boundaries, AI products were long confined to functioning merely as plug-ins embedded within WeChat, thereby preventing them from achieving any truly groundbreaking functional innovations. Since the beginning of this year, Tencent has ramped up promotional efforts to drive traffic to its AI application, Yuanbao, within the WeChat ecosystem; however, due to user complaints, certain access permissions for the application have subsequently been restricted.
The stark contrast between WeChat’s “massive user base” and the “untapped potential for AI conversion” suggests that identifying the precise entry point could trigger an exponential surge in the value of that traffic. The deep monetization of this existing user base represents Tencent’s key strategic asset in its bid to reshape the industry landscape in the AI era.
The concept of AI Agents offers Tencent a perfect solution to this dilemma: it enables the transformation of WeChat into an AI portal—without necessitating any fundamental alterations to the core user experience of the platform itself.
WeChat has long since become an integral part of daily life; in a sense, the data and information held by WeChat may well provide the most accurate lens through which to analyze an individual’s behaviors and interactions.
One of the major hurdles facing the deployment of OpenClaw in overseas markets is the issue of permissions; to unlock its full potential and deliver true value, the platform requires extensive access and authorization. When integrated with products characterized by a high degree of vertical specialization, an AI agent operates within clearly defined boundaries regarding the information it can access and the feedback actions it can execute. In contrast, a widely integrated, all-encompassing application like WeChat offers AI agents the most expansive scope for development.
The foundational and context-specific permissions required by these agents can all be facilitated through WeChat’s open APIs, eliminating the need for users to download additional applications or grant redundant authorizations. Furthermore, WeChat’s tiered authorization system and privacy protection mechanisms can partially address the compliance challenges associated with AI agents.
Consequently, once AI agents demonstrated to Tencent the potential to balance “reliance on WeChat” with “breaking through limitations,” the company—eager to overtake its competitors—naturally seized upon this concept. By consolidating the various AI assistant features it had previously experimented with, Tencent launched the “Xia” series of conceptual products.
Rather than pursuing isolated technological breakthroughs, Tencent aims to transform its AI capabilities into an “intelligent enhancement layer” for WeChat, thereby enabling the platform to evolve from a mere “social tool” into an “intelligent task hub.”
By deeply integrating the user engagement time, social graph, and service ecosystem of WeChat’s 1.414 billion users with the autonomous execution capabilities of AI agents, a closed-loop “User-Scenario-Service” ecosystem is established—one that renders Tencent’s dominance over digital traffic and user attention in the AI era virtually unassailable.
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Objectively speaking, Tencent’s strategic positioning is grounded in clear logical considerations; it is not a case of blindly following trends, but rather a pragmatic choice that leverages the inherent advantages of its own ecosystem.
The primary issue with the current “shrimp farming” craze is that it elevates an open-source execution framework to the status of a full-fledged AI agent, using narrative hype to manufacture anxiety.
Industry consensus holds that a true AI agent must possess a complete, closed-loop autonomous capability encompassing “perception, planning, decision-making, execution, and reflection.” It should be able to autonomously deconstruct objectives, adapt to dynamic environments, orchestrate multiple tools, and iteratively optimize its performance without continuous human intervention.
OpenClaw has equipped AI with the “hands and feet” for execution, but it has not yet formed a fully autonomous “brain.”
OpenClaw’s information retrieval and decision-making outputs are heavily contingent upon the scope of its training data and the manually configured execution workflows. Consequently, it can only perform repetitive operations within predefined scenarios and lacks the capacity to grasp the true intent underlying a given task. Once removed from its preset environment—or when confronted with dynamic shifts or novel problems—its execution is prone to significant deviations. It cannot complete complex, open-ended tasks without human oversight, let alone demonstrate any semblance of autonomous consciousness.
The tech giants are, of course, fully aware that the current crop of “shrimp” products remains, in essence, merely AI assistants—still far removed from meeting the standards of true AI agents.
Furthermore, as a “weekend project” cobbled together by independent developers, OpenClaw suffers from numerous deficiencies in its architectural design and default configurations. It exhibits an alarming 85% exposure rate to the public internet, and sensitive information is stored in plain text. Should such an open-source AI framework fall into malicious hands, it could be weaponized to launch large-scale attacks—a particularly grave risk given the sheer volume of core sensitive data housed within the WeChat ecosystem.
In the AI era, cybersecurity and data security constitute not only technical prerequisites and developmental imperatives but also inviolable legal red lines. When industry practitioners become overly zealous, one can hardly fault the relevant regulatory authorities for issuing a series of security warnings to cool down the “shrimp farming” frenzy.
The nationwide “shrimp farming” craze is a textbook example of industry hype—a fact that requires neither evasion nor apology.
At the core of this hype lies the industry’s collective impatience to achieve rapid success in the AI arena. Whether it be tech giants scrambling to secure strategic positioning, or service providers and developers building AI applications, everyone is eager to leverage this latest wave of “traffic frenzy” to accelerate technological adoption, attract capital investment, and inject fresh vitality into the market.
The true value of the “shrimp farming” craze lies in its ability to introduce the concept of AI agents to a broader audience through an engaging and low-barrier-to-entry format. Aloof, sophisticated AI technology has been transformed into an accessible, engaging “pet-rearing” style experience for the masses. In terms of breaking into the mainstream, the objective has certainly been achieved.
The “shrimp-rearing” craze will eventually subside; how to navigate its conclusion constitutes the true test for every player who has entered the game.
Those who merely jumped on the bandwagon may well make a hasty exit amidst the inevitable wave of uninstalls. The true industry giants, however, should have their contingencies in place—sifting through the chaos of a crowded, competitive landscape to gather actionable intelligence, identifying where potential bubbles are forming, eliminating false leads, and pinpointing the users’ most fundamental needs regarding efficient, intelligent execution tools.
Transforming short-term hype into long-term AI competitiveness—let’s hope the major tech firms are truly prepared.