Redefining AI Capability Boundaries/AI Chart

Manual Labor/Shoumei

Manually Edited/Jiaoshu

Produced by Unicorn Observer
In the second half of 2026, the competitive logic of the global AI sector underwent a fundamental shift. The multi-year race for large model parameters gradually came to an end, with the focus shifting to AI agents (Agent) that emphasize practical applications, becoming the main driver of industry growth.

In September, Meta's personal AI agent, Muse, quickly went viral on global social platforms due to its hardcore capabilities of autonomous web-wide retrieval, cross-platform task execution, and full-link closed-loop services, becoming a phenomenal AI product. Unlike traditional AI tools that passively respond and are limited to shallow content generation capabilities, Muse truly has been achieved (achieves) the leap from "information interaction" to "autonomous action," allowing ordinary users to intuitively experience AI's ability to independently complete full-process tasks in life, consumption, and work.

The explosive popularity of this product is not just a fleeting trend but a symbolic turning point in the global AI industry's iteration, officially declaring the industry's entry into the Agent implementation era. Muse's disruptive capabilities have not only refreshed the market's perception of personal AI agents but also deeply disrupted the domestic internet industry pattern (landscape), forcing leading tech giants like ByteDance, Alibaba, Tencent, and Baidu to accelerate their strategic adjustments and collectively increase their bets on the personal AI agent sector.

Given the significant differences in internet ecosystems, compliance systems, and business rules between China and foreign countries, the domestic market will not replicate the development model of overseas Muse. Instead, a full-scale Agent industry battle with Chinese local characteristics, centered around technology, scenarios, and ecosystems, has already begun in full swing.

01 The Underlying Logic Behind Muse's Viral Success

Before Muse's debut, mainstream AI products in the market were limited to a passive "question-and-answer" interaction mode. Whether it was general-purpose large models or various AI assistants, their core value only to stay (remained at) shallow scenarios such as information answering, content creation, and simple office assistance, unable to deeply integrate into real internet service systems, let alone complete complex closed-loop tasks.

Muse's emergence has completely broken this industry shackle, reconstructing the product form and value boundaries of personal terminal AI, and setting a new benchmark for the global AI industry's implementation.

As a universal-level personal AI agent launched by Meta's Super Intelligence Lab, Muse is built on the self-developed Muse Spark multimodal reasoning model, with its core industry positioning as an all-weather, omni-domain digital clerk for ordinary users.

Compared to traditional AI tools, its most core innovation lies in completely breaking free from the passive response interaction logic and achieving a complete capability closed loop of active perception, autonomous planning, and automatic execution. Traditional AI can only output information content and cannot connect with real internet scenarios, whereas Muse can autonomously break down task processes, traverse web-wide resources, complete screening, comparison, and implementation operations based on users' vague target instructions, without requiring step-by-step guidance or repeated intervention from users, truly achieving "one sentence to handle all-scenario affairs." Muse can access public web pages and simulate human browsing operations but is subject to anti-crawling and access permission restrictions from major platforms, unable to adapt unrestrictedly to all websites.

At the product experience level, Muse has completely lowered the barrier to using high-level AI agents, stripping away complex operations such as professional parameter debugging, model configuration, and permission deployment. Ordinary users can start using it with simple authorization, accompanied by sufficient free computing resources, achieving a zero-cost, inclusive experience. This lightweight, populist product design has allowed high-end AI technology to break out of its niche and quickly reach a vast number of ordinary users, laying the user foundation for its global viral success.

More critically, Muse's core value focuses on "reducing costs and improving efficiency for users," possessing strong perceivable commercial value. In consumption scenarios, it can break through information barriers on single platforms, avoid merchant markups and false discounts, and precisely lock in the best options across the web. In life and light office scenarios, it can replace humans in completing massive retrieval, comparison, and coordination work. After a large number of real-world test cases spread on social platforms, a word-of-mouth effect quickly formed, propelling Muse to the top of the global AI sector's popularity charts.

The fact that platforms like Amazon immediately banned Muse's crawler permissions and restricted data scraping also Side verification (indirectly confirms) the product's disruptive impact on traditional internet traffic barriers and platform profit models, further solidifying its industry benchmark status.

02 Domestic Tech Giants' Layout Paths

Muse's phenomenal viral success has made the domestic internet industry fully aware of the ultimate implementation form of personal AI agents and validated the commercial feasibility of C-end general-purpose Agents, making personal agents a core strategic sector for domestic leading tech giants.

A consensus has formed within the industry that AI Agents are the next-generation internet interaction Entrance (gateway) after mobile apps and mini-programs, set to completely reconstruct users' digital lives and consumption patterns. However, unlike Meta's aggressive approach of full web openness and boundaryless implementation, domestic tech giants generally exhibit a posture of high importance but cautious implementation, active layout but refusal to blindly replicate, with all product layouts deeply aligned with domestic compliance systems, closed App ecosystems, and local business landscapes.

The reason no one in China replicates the overseas Muse model stems from three insurmountable practical constraints. The first is compliance red lines. Domestic well-established data security and personal information protection regulations explicitly prohibit unauthorized crawler scraping, cross-platform illegal data acquisition, and other behaviors. Muse's reliance on web-wide penetration and unauthorized data scraping models is completely illegal for implementation in China.

The second is ecological constraints. Overseas internet is centered on an open web page ecosystem, with strong interconnectivity of data and services across the web. In contrast, China has a typical App walled garden ecosystem, with data, services, and payment systems from major platforms mutually isolated, lacking an open, all-domain operating environment.

The last is commercial interest constraints. Domestic leading tech giants are themselves the builders and beneficiaries of platform ecosystems. The cross-platform Agent's ability to conduct undifferentiated price comparisons and traffic diversion would directly impact their core revenue businesses in e-commerce and local life services, necessitating a self-protective, closed-loop development strategy. Based on these constraints, domestic tech giants have all chosen differentiated layout routes based on their own ecosystems, prioritizing compliance, and focusing on scenario implementation.

ByteDance is the most active domestic player in the personal Agent sector, closest to meeting the needs of mass users.

According to industry media reports, after Muse went viral, ByteDance quickly accelerated its internal personal agent project codenamed Spell, which has not been officially released yet. Built on the core capabilities of the mature Doubao mobile assistant, it jumps out of the overseas web crawler technical path and specifically adapts to the App-dominated usage scenarios in China, focusing on system-level cross-application automation operations.

Facing the risk control and interception barriers from major e-commerce and local life platforms, ByteDance did not blindly breach compliance boundaries but adopted a strategy of "prioritizing within the ecosystem, expanding externally in compliance," first fully connecting its own ecosystem closed loops such as Douyin, Douyin Mall, and local life services, then expanding third-party compliant scenarios through official collaborations, seeking a balance between user experience and platform commercial interests. This is also the product layout direction in China currently closest to Muse's "universal agency" experience.

Alibaba adheres to a steady and conservative layout approach, deeply cultivating its own ecosystem. It was the earliest domestic player to enter the personal Agent sector and maintains a firm strategic stance in response to Muse's viral success.

Unlike ByteDance's omni-domain expansion approach, Alibaba completely abandons cross-platform penetration models and focuses on building intelligent butler capabilities within the Alibaba ecosystem. Relying on the Tongyi Qianwen large model, it fully integrates Agent capabilities across all its own products, including Taobao, Alipay, Gaode, Fliggy, and Ele.me, covering full-scenario closed loops in shopping, consumption, commuting, life payments, and local services. With a complete e-commerce transaction, fulfillment, delivery, and payment settlement system, Alibaba's Agent capabilities can achieve complete task implementation without relying on external resources, providing users with precise intelligent shopping guidance, optimal consumption plans, and fully automated fulfillment services.

Although the closed ecosystem nature prevents it from offering web-wide price comparisons and cross-platform services, its ultimate (ultimate) in-station service experience can effectively enhance platform user retention and transaction conversion, firmly safeguarding its core positions in e-commerce and local life services. It represents a relatively mature Agent layout model in China with strong compliance and commercial implementation.

Tencent maintains a cautious and optimistic attitude in the Agent sector, adhering to development principles of scenario priority, compliance first, and controllable risks. According to industry reports, Tencent is parallelly laying out multiple intelligent agent product lines for both enterprise and personal ends, with the enterprise-end WorkBuddy already having relevant products launched, while the personal-end R&D projects have not been officially released to the public yet. The overall core relies on the WeChat super ecosystem for implementation, focusing on lightweight, low-risk service scenarios and firmly avoiding controversial operations such as unauthorized crawling and cross-platform data scraping.

Tencent's R&D approach for personal intelligent agents leans towards integrating with WeChat's social, mini-program services, and local life systems, focusing on lightweight agency tasks for daily trivialities, emphasizing service convenience rather than disrupting all-domain consumption decisions. Meanwhile, Tencent continues to strengthen its own ecological barriers, strictly preventing external AI Agents from scraping WeChat user data and mini-program resources. While developing its own intelligent agent services and optimizing user experience, it firmly safeguards the traffic advantages of its super gateway, with an overall layout that progresses steadily while focusing on deep cultivation of niche scenarios.

03 Who Will Be China's Version of Muse?

Given the ecological differences between Chinese and foreign internet environments, domestic compliance rules, and the layout rhythms of leading tech giants, completely replicating the overseas Meta Muse product with full web openness and neutrality has no implementation possibility in the domestic market.

However, the product trend of "AI autonomous agency, full-link implementation" validated by Muse is irreversible. A Chinese version of Muse adapted to the local environment, meeting user needs, and complying with commercial rules is likely to emerge in the domestic market. Moreover, local intelligent agents will form essential differences from overseas products in ecological logic, compliance systems, and commercial value, forging a unique localized development path.

Considering five core dimensions—technical iteration capability, C-end product refinement experience, user base, scenario coverage breadth, and ecological adaptability—from an industry logic perspective, ByteDance is currently the player most likely to launch a national-level Chinese version of Muse. Compared to other tech giants, ByteDance has deep roots in the C-end internet for years, possessing a mature mindset for creating hit products, excelling at simplifying product barriers, refining mass user experiences, and meeting the practical, lifestyle needs of ordinary users.

At the same time, ByteDance's massive user base and rich scenarios in short videos and local life services provide sufficient testing space and data support for the continuous iteration and scenario implementation of intelligent agents.

Although Alibaba possesses mature commercial closed loops and implementation capabilities, its product ecosystem is overly closed, only serving in-station scenarios with insufficient universality and inclusiveness, making it difficult to become a universal intelligent agent covering the entire population. It can only deeply cultivate the vertical e-commerce sector. Tencent focuses on lightweight social service scenarios with limited functional coverage, while Baidu's center of gravity (focus) leans towards the B-end market. Neither company possesses the comprehensive advantages to create a national-level C-end Agent product, making it unlikely to match ByteDance's development potential in the short term.

The environmental differences between Chinese and foreign markets ultimately create core trait differences between the Chinese version of Muse and its overseas counterpart, spanning three core dimensions: product ecology, compliance logic, and commercial value. At the ecological logic level, overseas Muse relies on the open internet web page ecosystem, possessing absolute neutrality, able to traverse all web platforms without discrimination and break all information barriers. Its core value lies in dissolving platform monopolies and empowering user decision-making.

In contrast, the Chinese version of Muse is a typical ecosystem-dependent product, implemented based on the closed ecosystems of tech giants. All task executions and service calls are based on compliant cooperation interfaces, unable to privately acquire third-party platform data, lacking absolute web-wide neutrality. Product services prioritize adapting to the ecological systems and commercial layouts of their affiliated platforms.

Therefore, from an industry reality perspective, the domestic AI Agent sector will ultimately not replicate the overseas outcome of a single hit product dominating the market. Instead, it will form a stable industry pattern (landscape) where multiple strong players coexist, ecological divisions exist, and scenarios are fragmented. Major leading tech giants will rely on their core ecological advantages to continuously deepen vertical scenario intelligent agents, building differentiated product barriers. There will be no universal super intelligent agent capable of monopolizing the entire web market.

As the industry's compliance system continues to improve and inter-platform ecological cooperation gradually opens up, future local intelligent agents are expected to gradually break through local ecological barriers within a compliant framework, achieving limited cross-platform collaborative services and continuously enhancing product universality and practicality.

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