Agentic AI Course: Stage 23 — Lesson 1: Introduction to AutoGen, Semantic Kernel and Microsoft Agent

This lesson introduces three distinct AI agent frameworks: AutoGen, Semantic Kernel, and Microsoft Agent Framework. Rather than being interchangeable options, each framework serves different purposes in agentic AI development. The lesson establishes foundational understanding of how these frameworks differ in architecture, capabilities, and use cases for building multi-agent systems.

Key Points

• •AutoGen, Semantic Kernel, and Microsoft Agent Framework are complementary, not interchangeable tools for agent development
• •AutoGen specializes in multi-agent orchestration and conversation patterns between autonomous agents
• •Semantic Kernel provides a unified abstraction layer for integrating LLMs with plugins and external services
• •Microsoft Agent Framework offers enterprise-grade agent development with structured workflows and governance
• •Understanding framework differences is critical for selecting the right tool for specific agentic AI use cases
• •Each framework has distinct strengths in areas like scalability, flexibility, and integration capabilities
• •Multi-agent systems require careful consideration of communication patterns and agent coordination mechanisms

Workflow Diagram

Concepts