In this episode, we break down the real reason most Copilots fail inside the Power Platform: context debt. Your model isn’t hallucinating because it’s dumb—it’s guessing because you starved it. We walk through a complete, repeatable context engineering blueprint for Copilot Studio and Power Automate, designed to eliminate hallucinations, reduce cross-tenant drift, and dramatically cut latency and cost. You’ll learn how to build the four-layer spine every enterprise Copilot needs: System Context, Retrieval, Tools, and Policies—plus the missing governance layer most teams overlook. What You’ll Learn 1. Why Your Copilot Fails (Context Debt)How missing system rules and vague identity cause inconsistent answersWhy ungrounded Dataverse data leads to hallucinated fieldsThe hidden impact of undefined tools and cross-environment driftHow governance gaps create policy violations and compliance risks2. Layer 1 — System Context That Doesn’t DriftThe System Message pattern used in real enterprise deploymentsIdentity, scope, refusal policy, schema awareness, and logging rulesHow to parameterize system context across Dev/UAT/ProdThe “six-line” system message formula that stops ambiguity cold3. Layer 2 — Retrieval That Grounds to DataverseHow to build a Dataverse-first schema indexWhy PDFs and document libraries aren’t grounding—and how to fix themChunking, security trimming, hybrid search, and caching for speedThe schema grounding checklist every agent needs4. Layer 3 — Tooling + Policy EnforcementTurning Power Automate flows into safe, least-privilege “agent verbs”How to encode preconditions, sensitivity flags, and refusal logicUsing DLP, Conditional Access, Purview, and MIP labels to prevent driftWhy you need an admin kill-switch (and how to add one)5. End-to-End Build (With Before/After Metrics)Step-by-step Copilot Studio + Power Automate buildSchema indexing, tool catalog, prompt wrappers, and environment bindingsBefore/after metrics: latency, token usage, hallucinations, policy adherenceReal example: correcting an invalid “fast-track to approved” requestKey TakeawaysModels don’t provide truth—they only predict text. You provide the truth.The four layers—System, Retrieval, Tools, Policies—eliminate drift and hallucination.Dataverse schema is the spine; documents are secondary.Governance isn’t optional: DLP, Conditional Access, and sensitivity labels define reality.A fully engineered context cuts latency, costs, hallucinations, and audit risk.Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-show-podcast--6704921/support.Follow us on:LInkedInSubstack

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