Why I Built an AI Agent Framework in .NET Instead of Python

Every AI agent framework you've heard of is in Python. LangChain, CrewAI, AutoGen, LangGraph — all Python. So when I started building AgentCraftLab, people asked the obvious question: why .NET? Here's the honest answer. The Enterprise Reality I work in enterprise environments where .NET is the backbone. The backend is C#. The CI/CD is Azure DevOps. The team knows C#, not Python. When we wanted to add AI agent capabilities, the options were: Use a Python framework — introduce a new language, new runtime, new deployment pipeline, new hiring requirements Use Semantic Kernel — Microsoft's answer, but it felt like wrapping OpenAI calls in enterprise abstractions Build something native — .NET 10, Microsoft.Extensions.AI, same stack the team already knows We picked option 3. The Problem with No-Code Agent Builders There's another category: visual no-code platforms like Flowise, Dify, n8n. They're great for demos. Drag some nodes, connect them, done. Until you hit the wall. Someone on Reddit p