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.

No sample repository to clone. The lecture walked through a real internal experiment: matching people to project requirements in a software house, using Azure OpenAI from an ASP.NET app, with Azure AI Search in the middle. At the end I also compared that path with Copilot Studio — mostly to show that Microsoft gives you more than one way to solve similar problems.