Core Insights - The report titled "White Paper on Intelligent Agent Internet" focuses on the development background, core challenges, system architecture, key technologies, evolution path, and application cases of the Intelligent Agent Internet, driven by breakthroughs in generative AI and large model technologies [1][8][18]. Group 1: Vision and Transformation - The Intelligent Agent Internet represents a paradigm shift from "connecting information" to "connecting intelligence," aiming to connect autonomous agents capable of perception, decision-making, and execution [1][8]. - The core characteristics of the Intelligent Agent Internet include autonomy, semantic understanding, and collective intelligence, which differentiate it from traditional internet architectures [18][20]. Group 2: Challenges of Existing Internet Architecture - Existing internet architectures face limitations in network capabilities, protocol capabilities, and control modes, which hinder the support for intelligent agent networks [25][29][33]. - The traditional IP architecture lacks content processing capabilities, making it difficult to support the semantic understanding and dynamic interactions required by intelligent agents [25][26]. Group 3: Key Technology Requirements - Key technology requirements for the Intelligent Agent Internet include providing network services for multiple agents, enhancing perception and network capabilities, enabling universal access management, and establishing a secure and trustworthy ecosystem [39][41][42]. - A standardized protocol system is essential for the Intelligent Agent Internet, similar to the TCP/IP model, to ensure interoperability among diverse agents and platforms [42][43]. Group 4: System Architecture - The proposed system architecture for the Intelligent Agent Internet is layered, consisting of a basic resource layer, interconnection function layer, collaboration management layer, and application enablement layer, forming a complete technical stack from infrastructure to application services [44][46].

Core Insights - AgentUnion has officially launched the Agent Communication Protocol (ACP), which is China's first practical communication protocol for agents [2] - ACP aims to facilitate communication and collaboration among agents, enabling efficient functionality reuse and cost-effective development of production-level agent applications [2][11] - The protocol defines various standards for agent identity, access mechanisms, data specifications, communication protocols, authorization systems, behaviors, and security, ensuring openness, reliability, and collaboration among agents [2][11] Summary by Categories Agent Architecture and Concepts - Each agent in the network is assigned a unique identity identifier known as AID (Agent Identifier), which is essential for accessing the agent internet [2][3] - Agents connect to the agent internet through Access Points (AP), which provide services such as identity authentication, addressing, communication, and data storage [4] - The communication protocol is based on HTTPS, ensuring secure data transmission and supporting large-scale concurrent services for enterprise-level deployments [5] Agent Discovery and Collaboration - ACP is designed to be friendly to agent search engines, allowing agents to easily discover each other without additional effort [7] - The protocol outlines the authorization and transaction processes for agent collaboration, facilitating the deployment of paid agent services [8] Evolution of Agents - The field of artificial intelligence is experiencing a significant leap in understanding agents, transitioning from a focus on chatbots to tools that solve specific business problems [10] - The emergence of ACP is seen as a catalyst for the transition from the tool expansion phase to the socialization phase of agents, enabling standardized communication and cross-domain collaboration [11] - AgentUnion aims to build an open protocol standard and decentralized collaboration network to support the free interconnection, secure interaction, and collaborative evolution of different agents [11]

Core Insights - The article discusses the transformation in the AI industry, emphasizing the shift from individual AI model usage to a collaborative network of agents, termed as "Agent collaboration network" [8][10][27] - It highlights the urgency for AI professionals to adapt their skills from prompt engineering to organizing and managing AI collaborations, as traditional skills may become obsolete [9][21][30] Group 1: Industry Trends - The AI landscape is evolving towards a multi-agent system where agents communicate and collaborate autonomously, moving away from reliance on human prompts [27][14] - The emergence of protocols like MCP (Multi-agent Communication Protocol) and A2A (Agent-to-Agent) is facilitating this transition, allowing for standardized communication between different AI systems [36][37] - Major companies like Alibaba, Tencent, and ByteDance are rapidly developing platforms that support these new protocols, enabling easier integration and deployment of AI agents [38][39] Group 2: Skills Transformation - AI professionals need to transition from being prompt engineers to "intent architects," focusing on defining task languages and collaboration protocols for agents [29][30] - The role of AI practitioners is shifting from using agents to organizing and managing multiple agents, requiring a new mindset akin to building a digital team [30][31] - There is a call for professionals to learn about agent frameworks, communication protocols, and how to register their tools as agent capabilities within larger networks [33][34] Group 3: Practical Applications - Various platforms and frameworks are emerging that allow AI professionals to practice and implement these new skills, such as LangGraph, AutoGen, and CrewAI [41] - The article emphasizes that the infrastructure for agent protocols is being established, providing opportunities for AI professionals to engage with these technologies [41][42] - The ongoing development of these systems is likened to the early days of TCP/IP, suggesting that those who adapt early will have a competitive advantage in the evolving AI landscape [42]