Stop Building Dumb Copilots: Why Agentic RAG Is Your Only Fix
Update: 2025-11-17
Description
🙋♀️ Who’s This For
On-Behalf-Of Auth • Row-Level Security • Column-Level Security • Purview Labels •
Verifier Agent • Multi-Agent Orchestration • Evidence-Linked Insights • Enterprise Copilot Architecture 🪞 Opening — “Your Copilot Isn’t Smart”
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Substack
- 🧠 CIOs / CDOs / Heads of AI — want auditable, verified, compliant answers
- 🏗️ Enterprise & Data Architects — designing Azure-based copilots with real reasoning
- 📊 BI / Analytics Leads — merging Fabric metrics + SharePoint context
- 🛡️ Security & GRC Teams — enforcing OBO auth, RLS/CLS, Purview governance
- ⚙️ Ops & Product Leads — need decisions, not hallucinations
On-Behalf-Of Auth • Row-Level Security • Column-Level Security • Purview Labels •
Verifier Agent • Multi-Agent Orchestration • Evidence-Linked Insights • Enterprise Copilot Architecture 🪞 Opening — “Your Copilot Isn’t Smart”
- Copilot = “well-dressed autocomplete,” not true intelligence
- Classic RAG → single query, single context window, zero reasoning
- Enterprises need multi-source reasoning (Finance + Fabric + SharePoint + external)
- Without agentic retrieval → fragmented context + hallucinated insights
- Agentic RAG fixes this: plans, cross-checks, validates before answering
- RAG = retrieve → prompt → generate → stop
- No memory, planning, or contradiction detection
- Can’t join data across systems (Fabric, SharePoint, Power BI, email)
- Produces eloquent but shallow summaries with zero provenance
- Leads to poor decisions, compliance risk, and false confidence
- Enterprises need planning + verification, not bigger prompts
- Adds executive function to AI: RAG + planning + verification
- Three core roles:
- 🗺️ Planner → decomposes query & assigns tasks
- 🧾 Retriever Agents → pull structured and unstructured data
- ✅ Verifier Agent → checks citations & consistency
- Runs an adaptive reasoning loop → query → validate → refine → act
- Built on Azure AI Agent Service with:
- On-Behalf-Of authentication (OBO)
- Row-/Column-Level Security
- Full audit logging + traceability
- Continuous comprehension = no context amnesia
- SharePoint = corporate archaeology; Agentic RAG = knowledge orchestra
- Uses semantic embeddings + vector search for meaning, not keywords
- Honors Entra ID auth + Purview labels → security-trimmed results
- Every document touch logged → non-repudiation for robots
- Example: R&D query → Planner splits tasks → Fabric for numbers, SharePoint for context
- Verifier cross-checks and flags outdated data
- Outcome: qualitative insight + citations, not random summaries
- Fabric = quantitative truth layer; SharePoint = contextual memory
- Fabric Data Agent translates natural language → structured SQL
- OBO auth enforces RLS/CLS; Purview labels travel with data
- All queries logged and auditable in Fabric logs
- Planner uses Fabric first to set numerical boundaries, then SharePoint for context
- Data pruning by reason → fewer queries, higher relevance
- Auditors can trace every number back to its source + timestamp
- Governance scales with intelligence → trust built by design
- Decision latency crashes:
- R&D alignment → hours → minutes
- Audits → manual weeks → instant replay
- Manufacturing alerts → predictive and continuous
- Business benefits:
- Verified insights reduce risk
- Compliance automated by design
- Teams focus on interpretation, not copy-pasting
- Governance ledger: every retrieval, query, and decision traceable
- Real recklessness = building dumb copilots that can’t reason
- RAG without agency = obsolete
- Enterprises need systems that plan, verify, and act under your identity
- Agentic RAG = Azure AI Agent Service + Fabric Data Agents + SharePoint retrievers + Purview governance
- Decorative AI outputs text; Agentic AI produces understanding
- Proof of reasoning → proof of trust
- 🧭 Deploy Planner / Retriever / Verifier pattern in Azure AI Agent Service
- 🔒 Use On-Behalf-Of Auth + RLS/CLS + Purview integration
- 📂 Add SharePoint Retriever for semantic context
- 🧮 Add Fabric Data Agent for structured query reasoning
- 🔁 Include verification loops for citations & contradictions
- 🧾 Maintain complete audit logs for governance and compliance
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