By ByteBot
Microsoft released .NET 10 on November 12, 2025, marking the first Long-Term Support version to ship with a built-in AI Agent Framework. The framework unifies Semantic Kernel and AutoGen, two previously separate libraries, into a single toolkit designed to make building AI agents as straightforward as creating a web API. Microsoft is betting that enterprises will build agentic AI systems in C# and .NET rather than switching to Python. The question is whether that bet will pay off in a world where Python dominates AI development.
The Agent Framework: Developer Request Fulfilled
The Agent Framework delivers on a developer request. The community asked Microsoft: why choose between AutoGen’s dynamic multi-agent orchestration and Semantic Kernel’s enterprise features when you could have both? The unified framework combines them with OpenTelemetry for observability, Entra ID authentication for security, and human-in-the-loop workflows for governance. It supports Agent2Agent protocols for cross-system collaboration and Model Context Protocol for dynamic tool connections.
Enterprises are already using it. KPMG is applying the framework for audit automation, and BMW is leveraging it for real-time vehicle data analysis. Semantic Kernel and AutoGen have entered maintenance mode, with all future development centered on the Agent Framework.
C# 14 and Performance Gains
C# 14 ships alongside .NET 10, introducing extension blocks that enable static methods and instance properties for other types, field-backed properties that eliminate boilerplate with a field keyword, and file-based apps that support script-like execution with #! directives on Unix systems.
Performance improvements span the stack. The JIT compiler delivers better inlining and devirtualization, while hardware acceleration includes AVX10.2 for x64 processors and ARM SVE support. NativeAOT produces smaller binaries with faster startup times, and Arm64 garbage collection optimizations reduce pause times by 8 to 20 percent. Microsoft claims this is the fastest .NET release yet.
.NET vs Python: The Strategic Tension
The strategic tension is obvious. Python owns AI and machine learning development through PyTorch, TensorFlow, LangChain, and CrewAI. It has a massive ecosystem of connectors and tools, an active open-source community delivering cutting-edge features, and a reputation for rapid prototyping.
Microsoft’s counter-argument is that enterprises already run on .NET and C#. Why maintain two stacks when you can build AI agents in the same language and infrastructure you use for everything else? The Agent Framework offers type safety that improves LLM code generation, enterprise features like security and compliance built in rather than bolted on, and seamless Azure integration for cloud deployment.
The bet is sound for organizations already invested in .NET. But Python’s momentum in AI development is undeniable. This is not about replacing Python for machine learning research. It is about keeping enterprise AI agent development inside the .NET ecosystem.
What Developers Should Do
For .NET developers, AI agent development is now first-class. There is no need to learn Python or maintain a separate AI stack. The LTS designation means three years of support until November 2028, making it safe for production systems.
For Python developers, the Agent Framework supports Python alongside C#, so the enterprise features might be attractive even without switching languages. For enterprises, the framework allows building AI agents in the existing technology stack with production-grade stability and built-in compliance.
The decision is straightforward if you are already on .NET. If you are running Python, the choice depends on whether enterprise integration and security matter more than innovation speed.
