Build Your First AI Agentic RAG in Azure AI Foundry 🚀 (Fun & Easy Guide)

In this video, I walk you through what AI Agents really are, how Agentic RAG (Retrieval-Augmented Generation with reasoning + actions) works, and how to build a fully functional AI Agent using Azure AI Foundry.

You’ll learn:

🧠 The basics of AI Agents — perception, reasoning, and acting in an environment
🔄 How ReAct (Reason + Act) works inside an AI Agent
📂 Connecting your own documents to your AI Agent with RAG
⚙️ Deploying GPT-4.1 as your agent’s “brain” in Azure AI Foundry
🏒 A real-world demo: building a hockey stats agent that answers player-specific questions
🐍 How to interact with your AI Agent using Python
🌐 How to call your agent using cURL commands from your local machine
💡 Tips for production setups, security, and observability

Whether you’re an AI enthusiast, developer, or architect, this tutorial will give you a solid foundation for building intelligent, document-connected agents—fast.

🎥 Previous video:
   • Step-by-Step Guide to RAG with LLMs Using ...  

🎥 Watch next:
   • Agentic RAG at Scale with Azure AI Search ...  

⏱ Timestamps
00:00 Intro – AI Agents & Agentic RAG
00:43 AI Agent basics explained
02:38 Creating an Agent in Azure AI Foundry
03:15 Deploying GPT-4.1 as the LLM brain
04:48 Real-world hockey stats example
06:46 Connecting documents (RAG)
11:16 Using the agent in Python
15:15 Using the agent with cURL
20:18 Wrapping up & next steps

💬 Have questions about building AI Agents? Drop them in the comments, and I might cover them in the next video.

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