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Building Scalable Agentic Systems

基础技能水平
更新时间 2025年12月
Discover what it takes to scale AI agents, with a little help from frameworks like MCP and A2A.
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TheoryArtificial Intelligence1 小时 30 分钟10 视频29 练习1,750 经验值12,187成就声明

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课程描述

Design and Develop Agents for Scaling

Learn how to design and develop AI agents with scalability in mind, following the three pillars of agentic scalability: modularity, robustness, and adaptability. Discover what makes a successful agent in production, and why so many struggle to get there.

Discover the Power of MCP and A2A

The Model Context Protocol (MCP) developed by Anthropic has revolutionized agent interoperability, creating a unified approach for connecting agents to data sources. The Agent-to-Agent protocol (A2A) developed by Google compliments MCP. Find out how these two frameworks can be combined to ensure your agent's integrations are scalable.

Implement Agent Testing and Deployment Best Practices

Before pressing the big red button and launching your agent into production, you've got to mitigate the risks that come with scaling. Learn how to create a robust testing framework to capture issues with components, integrations, performance, and security. Decide which deployment type is right for your agent by looking at the needs of the use case.

先决条件

Introduction to AI Agents
1

Designing Scalable Agents

Discover what makes a successful AI agent in production (and how many of them fail on the way!) Learn about the key agentic design principles to set up your agents for scaling, including robust infrastructure and tooling, modular design architecture, and continuous evaluation and feedback loops.
开始章节
2

Developing Agents for Scalability

3

Deploying Agents into Production at Scale

Time for production, but not so fast! Build a robust testing framework to give you confidence that the AI agent will continue to perform in production. Choose the best deployment strategy for your use case, and learn how to integrate real-time data sources with your agentic system.
开始章节
Building Scalable Agentic Systems
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