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If you’ve been curious about how to take your AI agent workflows from development to deployment, this new tutorial is for you. In my latest video, I walk you through the process of building declarative & hosted agents inside Visual Studio Code and then show you how to publish them directly to Microsoft Foundry (Preview). 🎯 What you’ll learn in the video: - How to set up declarative agents in VS Code - How to set up hosted agents in VS Code - Hosting workflows for scalable deployment - Publishing agents seamlessly to Microsoft Foundry - Why Foundry is becoming the go-to platform for enterprise-ready AI agents Whether you’re a developer experimenting with agent-based systems or an AI enthusiast looking to understand Microsoft’s latest tools, this tutorial will give you a clear, step-by-step guide to get started. 👉 Watch the full video here 📌 Don’t forget to like, comment, and subscribe for more tutorials on building intelligent agents with Microsoft Foundry!

If you’ve been exploring Microsoft Foundry and wondering how to actually run those declarative agent workflows you keep hearing about… this video is for you. I break down exactly how to view, run, and test declarative workflows inside VS Code — no fluff, just practical steps. You’ll learn how to open workflow files, understand agent logic, and test everything with real-world examples. Whether you're building multi-agent systems or just curious about how Foundry works, this tutorial will help you get hands-on fast. 🎯 What’s inside the video: - How to open and explore workflows in VS Code - Running workflows with Microsoft Foundry - Testing agent logic and human-in-the-loop steps - Tips for debugging and refining your setup 👉 Watch now: Happy learning!

Why Foundry Is a Big Deal AI is moving fast, and Microsoft Foundry is one of the biggest updates you should know about. It’s not just another platform—it’s a new way to build AI agents that can actually do things. Instead of being limited to answering questions, these agents can plan, reason, connect to apps, and pull knowledge from your company’s data. If you’ve ever wished your chatbot could act more like a teammate, Foundry is where that shift happens. Agents: Smarter Than Assistants Traditional assistants were reactive—they waited for you to ask something. Foundry agents are proactive. They can: - Understand intent beyond keywords. - Plug into tools and apps. - Pull info from knowledge bases like Foundry IQ . - Execute tasks without constant supervision. Think of them as digital interns who never get tired and don’t need coffee breaks. Tools: Giving Agents Superpowers Tools are what make agents useful. They’re the “hands” that let agents interact with the world. With Foundry Tools...

In this full tutorial, I’ll walk you through the complete workflow of creating an MCP (Model Context Protocol) server, deploying it on Azure App Service, and integrating it with AI agents using the AI Toolkit in Visual Studio Code. Whether you're a developer, AI enthusiast, or cloud architect, this video covers everything you need to: ✅ Build your MCP server ✅ Deploy it to Azure App Service  ✅ Secure and scale your server for production ✅ Connect it to AI agents for real-time tool invocation ✅ Troubleshoot, optimize, and monitor your deployment   If you're more interested in reading, then here is my detailed blog on MEDIUM

Big news in the AI world! Azure AI Foundry has officially been rebranded as Microsoft Foundry. This isn’t just a name change — it’s a shift in how developers and enterprises will build, deploy, and scale AI. In my latest video, I break down: 🔄 What’s new in Microsoft Foundry ❌ What’s been retired or changed 💡 Why these updates matter for your workflows 👉 Watch the full breakdown here: If you’re working with AI agents, cloud workflows, or enterprise integrations, this update is one you don’t want to miss. Alternatively, if you're more interested in reading, then here is my detailed blog on MEDIUM .

 🎬 Watch the Magic Happen — In Just Minutes Curious how you can turn plain English into a full-blown architecture diagram? In my latest video, I show you exactly how to auto-generate cloud diagrams using natural language and LLMs — no Visio, no manual layout, just smart markdown and AI. You’ll see: - How to describe your system in instructions.md - How the LLM interprets and builds the diagram - How to visualize Azure components, workflows, and tiers instantly 👉 Watch now and see how this technique can save you hours and make your documentation smarter: Auto-Generating Architecture Diagrams Using LLMs Once you try it, you’ll never diagram the old way again. If you're more interested in reading then here is my detailed blog: MEDIUM

Ever built an AI agent and thought,  “Wait… I don’t want it to actually run that tool yet”?  That’s where dry-run agents come in — and in this video, I show you exactly how to build one using the Microsoft Agent Framework. You’ll learn how to simulate tool usage without executing anything. It’s safe, smart, and perfect for testing workflows, debugging logic, or getting human approval before action. Whether you're a dev, a student, or just curious how AI agents “think before they act,” this tutorial breaks it down step-by-step — with real code, visuals, and a fun twist. 👉 Watch now and see how dry-run agents can transform your AI workflows — safely and brilliantly.