Core Concept - The article discusses the emergence of the "Agentic Web," a new paradigm in internet usage where AI agents autonomously complete tasks based on user-defined goals, marking a significant evolution from traditional web interactions [1][3]. Group 1: Evolution of the Web - The internet has undergone three major paradigm shifts over the past thirty years: from a keyword-driven "directory web" in the PC era, to a recommendation-driven "content explosion" in the mobile era, and now to an "action network" driven by AI agents [5][9]. - In the PC Web era, users actively searched and clicked through static pages, while in the Mobile Web era, users became consumers of algorithmically recommended content [7][8]. - The Agentic Web represents a shift where AI agents execute tasks autonomously, transforming the web from a static information repository to a dynamic ecosystem of actionable resources [9][10]. Group 2: Definition and Structure of Agentic Web - The Agentic Web is defined as a distributed, interactive internet ecosystem where AI agents, powered by large language models (LLMs), continuously plan, coordinate, and execute goal-oriented tasks [11][13]. - Users interact with the web by delegating tasks to AI agents, which can autonomously manage complex processes such as travel planning or data retrieval [13][15]. Group 3: Core Dimensions of Agentic Web - The structure of the Agentic Web can be understood through three core dimensions: intelligence, interaction, and economy [16]. - AI agents must possess cognitive abilities, including context understanding, long-term planning, and adaptive learning, to function effectively within this new paradigm [17]. - The interaction dimension emphasizes semantic-based communication between agents, allowing for collaborative task execution and negotiation [18]. - The economic dimension introduces the concept of "Agent Attention Economy," where the focus shifts from human clicks to AI agent interactions, leading to new advertising and service models [19][20]. Group 4: Application Scenarios - The Agentic Web enables three primary types of tasks: transactional (e.g., booking flights), informational (e.g., generating research summaries), and communicational (e.g., multi-agent negotiations) [20][21]. - In transactional scenarios, users can simply state their needs, and AI agents will autonomously complete the necessary steps, enhancing efficiency [22]. - Informational agents act as continuous research assistants, tracking developments in specific fields and synthesizing information over time [24]. - Communicational capabilities allow agents to collaborate and negotiate with one another, forming complex systems that can manage tasks across different domains [26]. Group 5: Challenges and Future Considerations - The implementation of the Agentic Web faces several systemic challenges, including enhancing AI capabilities, restructuring network infrastructure, and redefining economic models [28]. - Key challenges include improving multi-step reasoning, managing memory and context, ensuring tool security, and developing effective learning mechanisms [29][30][32][34]. - The need for unified communication protocols and decentralized trust systems is critical for enabling effective collaboration among AI agents [37][38]. - The shift towards the Agentic Web may disrupt traditional advertising models and labor markets, necessitating new business strategies and social considerations [47][49]. Group 6: Conclusion - The Agentic Web signifies a transformative shift from a passive information space to an active action space, where AI agents play a central role in executing tasks and creating value [50]. - This paradigm shift not only enhances efficiency but also redefines the relationship between humans and machines, as well as the economic structures of the internet [51].

Core Viewpoint - The article discusses the emergence of the "Agentic Web," a new paradigm in internet usage where AI agents autonomously complete tasks based on user-defined goals, marking a significant shift from traditional web interactions [3][6][57]. Group 1: Paradigm Shifts in the Web - The internet has undergone three major paradigm shifts: from a keyword-driven "directory web" in the PC era, to a recommendation-driven "content explosion" in the mobile era, and now to an "action network" driven by AI agents [8][9][15]. - In the Agentic Web, the role of the web transitions from being an information repository to an ecosystem of actionable resources for AI agents [13][15]. Group 2: Definition and Structure of Agentic Web - The Agentic Web is defined as a distributed, interactive ecosystem where AI agents, powered by large language models (LLMs), continuously plan, coordinate, and execute goal-oriented tasks [16][17]. - Users interact with the web by delegating tasks to AI agents, which autonomously handle the execution of these tasks [20][21]. Group 3: Core Dimensions of Agentic Web - The structure of the Agentic Web can be understood through three core dimensions: intelligence, interaction, and economy [24][28]. - The "Agent Attention Economy" signifies a shift in focus from human clicks to AI agent interactions, changing the metrics of commercial competition [29]. Group 4: Application Scenarios - The capabilities of the Agentic Web can be categorized into transactional, informational, and communicational tasks, enabling AI agents to perform a wide range of functions from booking tickets to conducting research [30][31]. - In transactional tasks, users can simply state their needs, and AI agents will autonomously complete the entire process, enhancing efficiency [33]. Group 5: Challenges Ahead - The implementation of the Agentic Web faces systemic challenges, including the need for improved AI capabilities, robust network infrastructure, and a redefined economic model [42][43]. - Key challenges include ensuring the reasoning and memory capabilities of AI agents, managing security risks associated with external tools, and establishing effective communication protocols for multi-agent collaboration [44][51]. Group 6: Socio-Economic Implications - The rise of the Agentic Web poses significant implications for traditional advertising models, labor markets, and economic structures, necessitating a reevaluation of how value is created and distributed in the digital economy [56][58]. - As AI agents become more prevalent, there is a pressing need to address the potential displacement of jobs and ensure equitable economic benefits [56][58].