Semantic Kernel vs AutoGen: Building Scalable Multi-Agent AI Systems on Azure AI Foundry

Description

Semantic Kernel vs AutoGen | Building Multi-Agent AI Systems on Azure AI Foundry In this video, we explore how to build scalable and intelligent multi-agent AI workflows using Microsoft Azure AI technologies. You’ll discover: - The difference between single-agent and multi-agent architectures - Connected Agents vs Semantic Kernel vs AutoGen - How Semantic Kernel orchestrates enterprise AI workflows - How AutoGen enables dynamic agent collaboration - Human-in-the-loop (HITL) systems - AI planning, memory, tool calling, and orchestration - Enterprise-grade AI automation patterns - How Azure AI Agent Service integrates with advanced agent frameworks This video is ideal for: • AI Engineers • Cloud Architects • Azure Developers • Solution Architects • Data Scientists • Enterprise AI Leaders • Students preparing for AI-102 Certification Technologies Covered: 🔹 Azure AI Foundry 🔹 Azure AI Agent Service 🔹 Semantic Kernel 🔹 AutoGen 🔹 OpenAI Models 🔹 Multi-Agent Systems 🔹 AI Orchestration 🔹 Tool Calling & Planning Whether you're building autonomous enterprise workflows, intelligent copilots, or next-generation AI systems, this session provides a practical understanding of modern AI agent orchestration. 📌 Don’t forget to Like, Share & Subscribe for more Azure AI, Cloud, Data Engineering, and Generative AI content. #AzureAI #SemanticKernel #AutoGen #AIAgents #AzureFoundry #GenerativeAI #ArtificialIntelligence #CloudComputing #AIEngineering #MachineLearning #AI102 #EnterpriseAI #OpenAI #MultiAgentSystems #Python #CSharp #MicrosoftAzure