I had organized and presented “Scalable Multi-Agent AI with AutoGen” at Nashua CLOUD .NET User Group. This session explored the modern AI agent architectures, particularly using AutoGen.
What We Covered
The session was focused on demystifying modern AI agent architectures, particularly using AutoGen, an open-source framework from Microsoft designed for orchestrating multi-agent conversations with LLMs, tools, and human-in-the-loop workflows. Here’s a quick recap of the key topics:
- What Are AI Agents?
We explored the core traits that distinguish agents from simple chatbots—autonomy, perception, goal orientation, and tool usage. - Building Blocks of Modern AI Systems
From completion and chat to function calling, RAG, and agentic reasoning, we broke down how LLM systems are architected. - Agent Frameworks in the Microsoft Ecosystem
A deep dive into AutoGen alongside tools like Semantic Kernel, Azure AI Foundry, and Copilot Studio. - AutoGen Capabilities
Code generation, tool orchestration, customizable agent roles, multi-agent collaboration, and human supervision. - Model Context Protocol (MCP)
We walked through a real-world agent interaction scenario using MCP to access web services via structured agent communication.
Missed the Demo?
No worries—you can find presentation slides and sample code from the session below:
📂 Download the Presentation (PPTX)
💻 Get the Sample Code on GitHub
Until next time—keep building, keep learning!