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Agent2Agent (A2A) Protocol Fundamentals
Rating: 4.3 out of 5(373 ratings)
1,798 students

Agent2Agent (A2A) Protocol Fundamentals

Learn the core mechanics of Google’s A2A Protocol, multi-agent collaboration, AI architecture, and real-world use cases.
Created byMayfair Real Estate Institute
Last updated 4/2025
English
English [Auto],French [Auto],

What you'll learn

  • Understand the architecture and core functions of Google’s Agent2Agent (A2A) protocol.
  • Learn how multi-agent systems communicate, share memory, and collaborate on complex tasks.
  • Analyze how Google uses A2A with models like Gemini, PaLM, and Bard.
  • Design basic agent-based workflows using principles of delegation and modularity.
  • Identify use cases where A2A can improve productivity, scalability, and coordination.
  • Gain the ability to map out and evaluate multi-agent collaboration systems in real-world applications.

Course content

4 sections • 16 lectures • 1h 51m total length

  • What Is Google’s Agent2Agent Protocol (A2A)?5:04

    Google's a2a protocol enables specialized ai agents to collaborate using a standardized four-layer architecture—communication, coordination, security, and integration—scaling multi-agent collaboration.

  • The Rise of Multi-Agent AI4:33

    Explore how multi-agent AI systems coordinate specialized agents through a coordinator, using JSON-based protocols to split tasks, share results, and solve complex, dynamic problems.

  • How A2A Enables Complex Collaborative Workflows6:08

    Discover how the agent2agent protocol enables specialized ai agents to collaborate as a digital team, sharing information, delegating tasks, and making real time decisions for fast, accurate outputs.

  • How Google Uses A2A in PaLM, Bard, and Gemini5:05

    Explore how palm, Google's pathways language model, scales training across thousands of accelerators and 540 billion parameters, enabling Bard's natural language interaction and Gemini's multimodal reasoning.

  • Specialized Agents in Google A2A Ecosystem7:42

    Explore specialized agents in the Google A2A ecosystem, including the reasoning agent with chain-of-thought and problem decomposition. Leverage information retrieval, code generation, and vision analysis for real-time data and visuals.

  • The Role of A2A in Enabling Autonomous Multi-Agent Collaboration4:44

    Explore how the agent to agent protocol enables autonomous multi-agent collaboration, with a main agent coordinating subagents via a shared framework and the MCP server for dynamic task handoffs.

Requirements

  • No programming experience required. A basic understanding of AI, LLMs, or tech workflows is helpful but not necessary.

Description

The Agent2Agent (A2A) Protocol is revolutionizing how intelligent systems work together and this course gives you a front-row seat to the future of AI.

Whether you're a developer, researcher, or AI enthusiast, this course walks you through the foundations of the A2A protocol and how it enables multiple large language model (LLM) agents to communicate, collaborate, and complete tasks more efficiently. Designed with clarity and practicality in mind, you'll explore real-world examples of how Google uses A2A in technologies like Bard, Gemini, and PaLM.

We’ll start with the big picture what A2A is, why it matters, and how it fits into the evolution of AI agents. Then, we’ll break it down into core components: agent architecture, messaging layers, task routing, shared memory systems, and orchestration techniques. Along the way, you’ll gain hands-on knowledge to begin working with A2A-like systems in your own LLM workflows.

This course includes:

  • A2A system overview and agent design principles

  • Breakdown of how Gemini and Bard use agent collaboration

  • Practical insights on agent chaining, memory, and task delegation

  • Visuals, breakdowns, and downloadable diagrams

  • Extra: A glossary of multi-agent AI terms

By the end, you’ll have a deep understanding of how Agent2Agent protocols enable scalable, intelligent, and modular AI systems and how to apply those principles in your own tools or research.

No prior agent-based system experience needed just a strong interest in the next frontier of artificial intelligence.

Who this course is for:

  • This course is for developers, tech enthusiasts, AI researchers, and curious learners who want to understand how Google’s Agent2Agent (A2A) protocol works behind the scenes. It’s ideal for anyone interested in building or understanding scalable multi-agent AI systems without getting lost in overly technical jargon.

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