Microsoft Agent Framework: Revolutionizing Artificial Intelligence
Estimated reading time: 7 minutes
Key Points
- Microsoft Agent Framework is a new open standard for creating, deploying, and managing AI agents and multi-agent workflows.
- The framework supports both .NET and Python as primary SDKs, allowing for maximum interoperability and portability.
- It unifies previous work and research from Microsoft Semantic Kernel and Microsoft AutoGen.
- It is based on the pillars of open standards, extensibility, research channel, and production readiness.
- Promises seamless integration with leading model providers (Azure OpenAI, OpenAI, others) and commercial APIs.
- Minimizes boilerplate code and offers advanced state and memory management for conversational agents.
Table of Contents
What is the Microsoft Agent Framework?
The Microsoft Agent Framework is an open-source development kit and an execution environment designed to facilitate the creation, deployment, and orchestration of artificial intelligence (AI) agents and complex multi-agent workflows.
Released to the public in October 2025, this framework stands out for unifying advanced research such as Microsoft Semantic Kernel and AutoGen.
It allows developers to work in both .NET and Python, and supports different model providers, including Azure OpenAI and OpenAI.
Key Capabilities of the Framework
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AI Agents: Autonomous entities that understand the user, call APIs, and collaborate using popular model providers.
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Workflows: Orchestrated systems of agents, with advanced routing, nesting, and support for human interaction (human-in-the-loop).
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Orchestration Patterns: Sequential, concurrent, group debates, handoffs, and advanced agent reflection patterns.
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Based on Proven Technologies: Semantic Kernel, AutoGen, and Microsoft.Extensions.AI.
The Four Fundamental Pillars
- Open Standards and Interoperability – Facilitate the transfer of agents and workflows between environments, avoiding vendor lock-in (more details).
- Research Channel – Allows testing and scaling advancements in agent AI.
- Extensible by Design – You can add specific capabilities or connect your own tools.
- Ready for Production – Ready to deploy robust and scalable enterprise solutions.
Developer Experience
- Minimal Boilerplate: Functional prototypes with less than 20 lines of code.
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State Management: The framework has integrated agent threads that maintain context and memory (read more about memory in AI).
- Middleware: Extends and intercepts the agent’s dialogue and actions.
- Persistent and Dynamic Memory: Supports long conversations and complex tasks using advanced context providers.
Ecosystem and Use Cases
The Microsoft Agent Framework is portable and neutral, designed to facilitate the transition between platforms and avoid unwanted dependencies.
Thanks to open standards and robust interoperability, agents and workflows can easily move between environments.
With support for OpenAPI, integration with commercial APIs becomes faster and eliminates the need to create custom wrapper.
Conclusion and Microsoft’s Strategic Vision
In conclusion, the Microsoft Agent Framework represents the company’s clear commitment to an open, modular, and production-ready technological foundation in the world of AI agents.
With its strategic vision, Microsoft takes a step forward to establish itself as a leader in developing intelligent solutions ready for any environment.
What are you waiting for to dive into the exciting world of agents? You can start with the official resource guide on Microsoft Learn and explore tutorials and short videos to understand the flow and architecture of agents.
Keep exploring, keep learning, and stay tuned for the latest AI updates!
Frequently Asked Questions
What exactly is the Microsoft Agent Framework?
It is an open-source platform and development kit to create, orchestrate, and deploy artificial intelligence agents, integrating the best of Semantic Kernel and AutoGen.
Do I need to know Python or .NET to use it?
Not necessarily. While the framework is optimized for .NET and Python, you can integrate existing agents or build new ones from scratch in either of these environments.
Which LLM model providers are supported?
Supports major providers, including Azure OpenAI and OpenAI.
Is it extensible or integrable with other services?
Yes, its extensible architecture allows for expanding functionalities and connecting to APIs or systems, especially through OpenAPI.
Are there resources or tutorials to get started?
Yes, you can access official guides, videos, and quick steps from Microsoft Learn documentation and specialized channels.