Infra 软件的主要使用者，正从人类开发者变成 AI Agent。 a16 今年的年终预测中，也明确指出：Agent-native 的基础设施将成为未来的基本门槛。 如今的企业后端是为「一次人类动作对应一次系统响应」的 1:1 比例而设计的。它的架构无法让单个智能体「目标」在毫秒级时间内递归展开成 5,000 项子任务、数据库查询和内部 API 调用。 2026 年我们将见证「原生智能体」基础设施的崛起。下一代系统必须默认应对「惊群」模式；冷启动时间必须缩短，延迟波动必须收敛，并发 上限必须跃升数个量级。唯有能承受随之而来的工具执行洪流的平台，才能最终胜出。 但很明显，当下 Agent Infra 的基础设施并不完善，不管是代码的兼容性还是服务器的启动优化，甚至虚拟机的配置等，都还是为人类开发者的服务模式。 AI Agent 对 Infra 的要求，与人类完全不一样。 这其中存在很多新的机会和可能性。 Agent Infra 的现状如何，还有哪些问题没有解决，未来更多的可能性会在哪些场景？就这些问题，我们与腾讯云 Agent Infra 团队 和 Dfiy 的技术人员聊了 聊，希望能搞清楚一些事情。 ⬆️关 ...

鹭羽 发自 凹非寺 量子位 | 公众号 QbitAI 毋庸置疑！2025年title属于 「Agent元年」 。 要说Agent这把火，一直从年初烧到了年末—— 先是Manus，再到最近的豆包手机……Agent已然成为全行业的关注焦点。 而回顾这一年，也是 Agent从技术萌芽，走向工程化落地的关键一年 。 于是乎，量子位趁热打铁攒了场局，邀请来两位行业大拿——Dify开源生态负责人 郑立 和腾讯云云原生产品副总经理 于广游 做客，聊一聊 他们眼里Agent落地过程中的挑战、机遇和未来： 两位嘉宾还给出了一个高度一致的判断： 在智能体落地过程中，Agent Infra是关键一环。 郑立 ：其实这一年Agent发展吧，我能感受到就是 大传统和小传统 之间的鲜明张力。 大传统其实就比如说来自硅谷那些的宏大叙事，他们会许诺用全自动智能体取代白领，逻辑完美但实际落地的时候会有些水土不服。 那从小传统来看，会充满一些烟火气，比如我看到义乌商家使用AI自动回复客户，还有比如独立开发者会用工作流进行代码评审。 下面一起跟随量子位的视角，看看他们具体都说了些什么，知识密度之高，不要轻易眨眼。 从年初硅谷的宏大叙事，Agent ...

Core Insights - The article discusses the transition of AI into the "Agent Era," where AI moves from passive responses to proactive decision-making, becoming a crucial link between the digital and physical worlds [1] - AI Agents are reshaping industries by automating complex tasks across various sectors, supported by a sophisticated infrastructure that includes algorithms, models, and a full lifecycle support system [1] - By 2025, the AI Agent infrastructure (Agent Infra) is expected to experience significant growth, driven by breakthroughs in open-source large models and the flourishing ecosystem of Model Context Protocols (MCP) [1] Agent Applications and Challenges - AI applications in enterprises face five major pain points, particularly in automating workflows, which were previously limited by the capabilities of RPA [3][4] - The emergence of generative AI has led to the development of intelligent Agent applications that can handle complex tasks, but these applications often do not meet the needs of professional AI developers and businesses [5] - Key challenges include computational limitations for AI reasoning, high concurrency demands, and the complexity of configuring AI tools necessary for solving intricate problems [6][7] Infrastructure Developments - Major cloud providers are launching new generations of Agent Infra technologies to address the limitations of traditional serverless architectures, focusing on long-running tasks, session affinity, and enterprise-level security [12][18] - Innovations include AWS's AgentCore, Azure's AI Foundry Agent Service, and Google Cloud's Vertex AI Agent Builder, all aimed at enhancing the capabilities of AI Agents [12][13][14] - The new infrastructure aims to support continuous reasoning, complex state management, and flexible integration of various tools, which are essential for the effective deployment of AI Agents [22][24] Future Opportunities - The growing demand for Agent Infra presents opportunities for both established cloud giants and startups to innovate and meet the evolving needs of AI development [24] - There is a significant market for infrastructure products that lower development barriers and enhance usability, as the Agent ecosystem emphasizes collaborative development [24] - As the deployment of Agents becomes more streamlined, the industry anticipates a future where creating an Agent is as easy as assembling building blocks, indicating a shift towards a more integrated and efficient AI landscape [24]

Core Viewpoint - The article discusses the significant growth in the development and usage of Agents since 2025, leading to a surge in demand for Agent Infrastructure (Infra). The emergence of Agent-native Infra is reshaping the development paradigm, making it easier and faster for developers to create Agents [3][4]. Investment Theme 1: Environment - Environment provides a container for Agents to execute tasks, functioning as an Agent-native computer. Key areas include Sandbox and Browser Infra, which are crucial for Agent development and operation [13][18]. - Sandbox offers a secure virtual environment for Agent development, requiring higher performance standards such as faster startup times and stronger isolation. Companies like E2B and Modal are emerging in this space, providing AI-native microVMs and scalable cloud-native VMs respectively [20][21]. - Browser Infra enables Agents to operate effectively within web environments, allowing for large-scale browsing and manipulation of web pages. Browserbase is highlighted as a leading company in this area, balancing performance factors like bandwidth and speed [22][23]. Investment Theme 2: Context - Context is essential for Agents to plan and act effectively, providing necessary background information and tool usage methods. Key components include RAG, MCP, and Memory [26]. - RAG (Retrieval-Augmented Generation) enhances the accuracy and timeliness of Agents by integrating information retrieval with generative AI. Companies like Glean are recognized for their enterprise-level RAG solutions [29][30]. - MCP (Multi-Context Protocol) standardizes how Agents interact with external tools and services, with companies like Mintlify and Stainless simplifying the creation of MCP servers [31][32]. - Memory is crucial for maintaining continuity in Agent interactions, allowing for personalized and consistent behavior. Companies like Letta and Zep are developing solutions to enhance Agents' memory capabilities [34][36]. Investment Theme 3: Tools - Tools are vital for Agents to perform various tasks, with a focus on search, finance, and backend workflows. The number of tools available for Agents is expected to increase significantly [43]. - In the search domain, companies like Exa and 博査 are providing cost-effective and intelligent search solutions tailored for Agents [45][46]. - The finance sector presents opportunities for Agents to engage in transactions and monetization, with companies like Skyfire enabling payment capabilities for Agents [48][51]. - Backend workflow tools like Supabase and Inngest are simplifying the development process for Agents, allowing for rapid deployment and integration [54][56]. Investment Theme 4: Agent Security - Security is a critical aspect of Agent Infra, ensuring the safety and compliance of Agent actions. Companies like Chainguard and Haize Labs are providing security solutions tailored for Agent environments [57][59]. - The demand for security solutions is expected to grow as the Agent ecosystem matures, with a focus on dynamic intent analysis and real-time monitoring [60][61]. Appendix: Cloud Vendors in Agent Infra - Major cloud vendors like AWS, Azure, and GCP are actively developing products in the Agent Infra space, although no Agent-native products have emerged yet [62]. - Each vendor has introduced various solutions across Environment, Context, and Tools, but the focus remains on enhancing existing infrastructures rather than creating new Agent-native offerings [63][70].