Episode Details

Back to Episodes
Agentic RAG Copilot: Stop Building Dumb Copilots and Start Using Agentic RAG

Agentic RAG Copilot: Stop Building Dumb Copilots and Start Using Agentic RAG

Season 1 Published 5 months ago
Description
(00:00:00) The Limitations of AI Copilots
(00:00:23) The Flaws of Retrieval-Augmented Generation (RAG)
(00:02:05) The Linear Intelligence Fallacy
(00:05:07) Introducing Agentic RAG: The Evolution of AI Assistants
(00:09:48) Agentic RAG in Action: SharePoint Integration
(00:13:26) Structured Data Meets Unstructured Knowledge
(00:17:56) The Impact of Agentic RAG on Enterprise Decision-Making
(00:20:51) The Future of AI in Enterprises
(00:22:22) Subscribe and Enable Alerts

In this episode of M365.fm, Mirko Peters explains why most enterprise copilots are just “well‑dressed autocomplete” — and how Agentic RAG, built on Azure AI Agent Service, Fabric Data Agents, and SharePoint retrievers, is the only realistic way to get verified, auditable answers instead of pretty guesses.

WHAT YOU WILL LEARN
  • Why classic RAG (retrieve → prompt → generate → stop) fails for real enterprise decisions
  • How a Planner, Retriever Agents, and a Verifier Agent work together as an agentic system
  • How On‑Behalf‑Of auth, RLS/CLS, and Purview labels keep Agentic RAG inside your security and compliance guardrails
  • How SharePoint retrievers turn “corporate archaeology” into searchable, security‑trimmed context with full audit logs
  • How Fabric Data Agents translate natural language into governed SQL over your semantic models
  • How verification loops, evidence‑linked insights, and provenance turn AI output into something auditors and GRC can live with
  • A practical implementation checklist: Planner/Retriever/Verifier pattern, OBO auth, Fabric + SharePoint integration, and logging
THE CORE INSIGHT

RAG without agency is obsolete for enterprises. A single prompt over a single context window cannot join Fabric metrics, SharePoint documents, and external systems, let alone check itself for contradictions or stale data. Agentic RAG adds planning, multi‑agent retrieval, verification, and full governance so your copilot can reason across systems under the user’s identity and leave a complete audit trail behind every answer.

WHO THIS EPISODE IS FOR

This episode is ideal for CIOs, CDOs, Heads of AI, enterprise and data architects, BI leads, and security or GRC teams who need copilots that can actually be trusted in front of regulators, auditors, and executives. If your current copilots look great in demos but collapse on provenance, permissions, and verification, this conversation gives you a concrete blueprint for rebuilding them as Agentic RAG systems.

Listen Now