Mar 16
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Build production-grade multi-agent AI systems with the A2A protocol — 6 frameworks, 4 free models, from zero to capstone. In this lesson, we introduce the A2A Agent-to-Agent Protocol and confront the N² integration problem that breaks as multi-agent systems scale. This is Lesson 01 of the 16-part A2A Protocol course designed for Python engineers who want hands-on, production-ready skills. Instructor: Nilay Parikh Channel: LocalM Tuts Full Course: https://tuts.localm.dev/a2a Full Course on Youtube: https://www.youtube.com/playlist?list=PLJ0cHGb-LuN9JvtKbRw5agdZl_xKwEvz5 ⸻ Timestamps (Chapters) ⸻ 00:00 - Introduction & Course Overview 01:20 - The Agentic AI Communication Problem 01:48 - The N² Integration Problem 02:14 - What Is A2A? The Open Standard 02:42 - A2A vs MCP: Complementary Protocols 03:52 - Course Architecture: 6 Frameworks & 4 Models 04:38 - Course Roadmap: 16 Lessons 05:27 - What You'll Build ⸻ Resources & Links ⸻ 🔗 Course Page: https://tuts.localm.dev/a2a 💻 Example Code: https://github.com/nilayparikh/tuts-agentic-ai-examples 📄 A2A Spec: https://github.com/a2aproject/a2a-spec ▶️ Next Lesson: Why Agent2Agent Protocol? | Lesson 02 ⸻ About this Course ⸻ This 16-lesson course takes you from zero to a production-ready multi-agent AI system. You will implement the A2A protocol with six different frameworks — Microsoft Agent Framework, Google ADK, LangGraph, CrewAI, OpenAI Agents SDK, and Claude Agent SDK — and power each agent with free-tier or locally-run models. No expensive cloud APIs required. #A2A #Agent2Agent #AIAgents #MultiAgentSystems #AgenticAI #Introduction #MCP #Python #Tutorial #LocalM