Microsoft Agent Framework RC Brings Unified Agentic Development to .NET and Python
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Microsoft Agent Framework RC Brings Unified Agentic Development to .NET and Python

Rust Reporter
1 min read

Microsoft's Agent Framework reaches Release Candidate status, consolidating agent creation and orchestration across .NET and Python with stable APIs and multi-provider support.

Microsoft has announced that the Microsoft Agent Framework has reached Release Candidate status for both .NET and Python. This milestone indicates that the API surface is stable and feature-complete for what is planned in version 1.0, setting the stage for an upcoming general availability release.

For developers building AI-powered assistants or complex agentic systems, this release is a significant step toward a unified, production-ready toolset. The Microsoft Agent Framework is an open-source development framework designed to build, orchestrate, and deploy AI agents with a consistent programming model across .NET and Python. It succeeds earlier efforts such as Semantic Kernel and AutoGen, consolidating agent creation, orchestration primitives, and multi-provider support under a single SDK.

The framework supports common patterns for creating autonomous agents as well as workflows that combine multiple agents, and it integrates with a variety of AI model providers. Before this release candidate, developers experimenting with Microsoft's agent technologies had to piece together capabilities using Semantic Kernel or experimental multi-agent orchestrators. Those tools provided early building blocks for agent creation and function invocation, but lacked a stable, unified API suitable for enterprise-grade systems.

With this RC release, the framework's APIs and workflows are locked down, allowing teams to start production evaluation and implementation with greater confidence. The framework emphasizes simplicity and flexibility. Developers can create a basic AI agent in just a handful of lines in either Python or .NET, using client libraries to connect to various model providers.

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