Exploring Microsoft’s New Framework for Building Agentic AI Apps
John: Hey everyone, welcome back to the blog! Today, we’re diving into something exciting from the world of AI: Microsoft’s recent unveiling of a framework for building agentic AI apps. If you’re a tech enthusiast who’s curious about how AI is evolving beyond simple chatbots, this is going to be fun. Agentic AI refers to systems where AI agents can act autonomously, make decisions, and even collaborate with other agents to get things done. Microsoft just dropped this open-source framework to make it easier for developers to create these kinds of apps, and it’s generating a lot of buzz.
Lila: Whoa, John, that sounds advanced. I’m a beginner here—what exactly is an “agentic AI app,” and why is Microsoft getting into this now?
John: Great question, Lila! Think of agentic AI like a team of smart assistants that don’t just answer questions but actually take actions on your behalf. For example, an agent could book a flight, summarize reports, or automate workflows by reasoning through steps and using tools. Microsoft unveiled this framework a few days ago, and it’s called the Microsoft Agent Framework. It’s open-source, meaning anyone can use and contribute to it, and it supports building complex multi-agent systems with .NET or Python. If you’re into automation and want to compare tools that integrate with AI, our deep-dive on Make.com covers features, pricing, and use cases in plain English—worth a look for seeing how it pairs with agentic setups: Make.com (formerly Integromat) — Features, Pricing, Reviews, Use Cases.
The Basics: What Is the Microsoft Agent Framework?
Lila: Okay, so it’s for building these autonomous AI agents. But can you break it down? Is this like a toolkit, and who’s it for?
John: Absolutely, let’s keep it simple. The Microsoft Agent Framework is essentially a software development kit (SDK) and runtime environment that unifies tools for creating, orchestrating, and managing AI agents. It’s in public preview right now, as announced on the .NET Blog and other official channels. It builds on existing projects like Semantic Kernel and AutoGen, which Microsoft is consolidating into this one framework. This means developers—from beginners to pros—can build agents that reason about goals, call APIs, collaborate, and handle complex workflows without starting from scratch.
Lila: Semantic Kernel and AutoGen? Those sound familiar but technical. What’s the big deal with unifying them?
John: Good catch! Semantic Kernel is great for integrating AI into apps with plugins and memory, while AutoGen focuses on multi-agent conversations. By merging their strengths, the new framework simplifies everything into one package. According to Microsoft’s tech community hub, it’s designed to make AI agents production-ready faster, with built-in hosting, observability, and governance. It’s all open-source, so it’s accessible on GitHub, and it’s tied to Azure AI Foundry for cloud deployment.
Key Features and How It Works
Lila: Features sound key—can you list out the main ones? And maybe explain with an example?
John: Sure thing! Here’s a quick rundown of the standout features based on the latest updates from sources like InfoWorld and VentureBeat:
- Unified Orchestration: Easily manage multiple agents working together, like a team where one agent researches data and another analyzes it.
- Tooling and Integration: Supports calling external tools and APIs seamlessly, making agents more capable.
- Observability: Built-in monitoring to track what agents are doing, which is crucial for debugging and scaling.
- Cross-Language Support: Works with .NET and Python, so developers aren’t locked into one ecosystem.
- Governance: Features to ensure agents behave ethically and securely, especially in enterprise settings.
For an example, imagine building an app for customer service: One agent handles queries, another pulls from a database, and a third escalates issues—all orchestrated by this framework. It’s not just theory; Microsoft says it’s for real-world apps in sectors like healthcare or finance.
Current Developments and Trending Discussions
Lila: This is recent, right? What’s the buzz on X or in the news?
John: Spot on—it’s only been a few days since the announcement on October 1, 2025, based on posts from the Azure Dev Community and WinBuzzer. On X (formerly Twitter), developers are excited about how it retires AutoGen updates in favor of this unified approach, as noted by verified accounts from Microsoft devs. Trending discussions highlight its potential for scalable AI, with some users sharing early experiments. For instance, MarkTechPost reported it’s simplifying multi-agent systems, and Satya Nadella even mentioned it in talks about AI economics, emphasizing efficient workflows in Azure.
Lila: Any challenges or downsides popping up in these talks?
John: Fair point. While it’s promising, some devs on X are noting it’s still in preview, so there might be bugs or incomplete features. Governance is a plus, but ensuring agents don’t go rogue in complex setups is a concern. Plus, it requires some Azure knowledge for full power, which could be a barrier for total beginners.
Future Potential and Real-World Applications
Lila: Looking ahead, how could this change things? Any cool applications?
John: The potential is huge! This framework could democratize AI agents, making them as common as apps on your phone. Think automated research, personalized education, or even smart home systems that adapt on their own. In business, it might streamline operations in critical sectors, though always with safeguards. If creating supporting materials like slides for your AI projects feels overwhelming, this step-by-step guide to Gamma shows how you can generate presentations, documents, and even websites in just minutes: Gamma — Create Presentations, Documents & Websites in Minutes. It’s a great tool to visualize agentic AI concepts quickly.
Lila: That makes sense. But is it free, and how do I get started?
John: It’s open-source and free to use, with previews available via Azure AI Foundry. Check the official .NET Blog for tutorials—start small, like building a single agent, and scale up.
FAQs: Answering Common Questions
Lila: Before we wrap, let’s do some quick FAQs. What’s the difference between this and other AI frameworks?
John: Unlike general ones like TensorFlow, this is specialized for agentic workflows. It’s more about orchestration than raw model training.
Lila: Do I need to be a pro developer?
John: Not at all—it’s designed for all skill levels, with docs to guide you.
Lila: Any integration with other Microsoft tools?
John: Yes, it ties into Copilot and Azure services, plus free Copilot access for students as part of recent announcements.
John: Reflecting on this, Microsoft’s Agent Framework feels like a game-changer, bridging the gap between experimental AI and practical apps. It’s rooted in real developer needs, and I’m excited to see how it evolves with community input. If you’re tinkering with automation, don’t forget that Make.com guide I mentioned earlier—it’s a solid starting point for integrating with AI agents.
Lila: Totally agree, John! My takeaway is that agentic AI isn’t as intimidating as it sounds—with tools like this, even beginners like me can explore building smart systems. Can’t wait to try it out!
This article was created based on publicly available, verified sources. References:
- Microsoft unveils framework for building agentic AI apps | InfoWorld
- Introducing Microsoft Agent Framework (Preview): Making AI Agents Simple for Every Developer – .NET Blog
- Microsoft retires AutoGen and debuts Agent Framework to unify and govern enterprise AI agents | VentureBeat
- Microsoft Releases ‘Microsoft Agent Framework’: An Open-Source SDK and Runtime that Simplifies the Orchestration of Multi-Agent Systems – MarkTechPost