Description
What if anyone could automate Revit software without writing a single line of code? This session introduces an open-source AI agent that turns natural language into executable Revit operations. Built on retrieval augmented generation (RAG) and Model Context Protocol (MCP), it retrieves knowledge from Revit API Docs, generates C# code, and executes it inside Revit in real time. Key highlights include the following: There are no hardcoded rules the large language model (LLM) reasons from real API signatures. There are no preset commands never-seen operations are reasoned and created on the fly. Successful operations solidify into reusable templates non-developers replay them instantly. And there's a live Revit connection via TCP JSON-RPC with Roslyn dynamic compilation. No C# experience or plug-in background is needed. And there's no command library to maintain. Just describe what you want.
Key Learnings
- Discover the architectural difference between a grounded AI system and a prompt-only approach for Revit API code generation.
- Learn how to build a natural language command that triggers dynamic parameter selection from a live Revit model, without writing C# code.
- Compare first-run RAG reasoning against solidified tool execution and assess when each path suits a given operation.
- Learn how to implement tool solidification to convert a successful AI-generated Revit operation into a reusable cross-project template.
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