The project was a file-aware chat: upload internal documents, ask questions, get answers grounded in those files. We built it twice — first as classic RAG on Azure OpenAI plus Azure AI Search, then as an Azure AI Foundry Agent. The second path was better for file handling; the first path was easier to reason about in Terraform. Platform engineers will recognize the pattern: the product story moves faster than the IaC provider story.

I had joined a Databricks engagement from the Azure infrastructure side — Terraform, identity, pipelines — rather than from notebooks. The meetup was a compressed version of that delivery work. I am expanding the same material into a longer whitepaper with diagrams; this post is the short form from right after the talk.