The Copilot Assumption That's Holding You Back - Agentic RAG - M365.FM

Topics in this episode

Copilot Automation Dataverse agentic agents

Episode notes

Most people still think Microsoft Copilot is fundamentally a question-and-answer system: you ask something, it searches for information, and an LLM generates an answer. But that mental model is becoming outdated. Copilot is evolving toward an orchestration system that can determine where to search, evaluate what it finds, decide whether additional information is required, and increasingly take action based on the result. In this deep dive, we break down Agentic RAG, how it differs from traditional Retrieval-Augmented Generation, why multi-source enterprise questions expose the limits of single-shot retrieval, and what this architectural shift means for Microsoft 365, Copilot Studio, Microsoft Graph, Entra, Purview, MCP, governance, and enterprise AI strategy. WHY TRADITIONAL RAG WORKS - UNTIL IT DOESN'T Traditional Retrieval-Augmented Generation follows a relatively straightforward pipeline. A user's question is converted into an embedding, relevant chunks are retrieved from a vector database, those chunks are placed into the model's context, and the LLM generates an answer.