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].