Your cart is empty.
Keep shoppingAgent2Agent (A2A) Protocol Fundamentals
1,265 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
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.
Explore related topics
Course content
4 sections • 16 lectures • 1h 51m total length
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.