docs(architect): weekly KB update — 106 files refreshed (2026-04)

Updates across all 5 skills: ms-ai-advisor, ms-ai-engineering,
ms-ai-governance, ms-ai-security, ms-ai-infrastructure.

Key changes:
- Language Services (Custom Text Classification, Text Analytics, QnA):
  retirement warning 2029-03-31, migration guides to Foundry/GPT-4o
- Agentic Retrieval: 50M free reasoning tokens/month (Public Preview)
- Computer Use: Claude Sonnet 4.5 (preview) + OpenAI CUA models
- Agent Registry: Risks column (M365 E7), user-shared/org-published types
- Declarative agents: schema v1.5 → v1.6, Store validation requirements
- MLflow 3: 13 built-in LLM judges, production monitoring, Genie Code
- AG-UI HITL: ApprovalRequiredAIFunction (C#) + @tool(approval_mode) (Python)
- Entra ID Ignite 2025: Agent ID Admin/Developer RBAC roles, Conditional Access
- Security Copilot: 400 SCU/month per 1000 M365 E5 licenses, auto-provisioned
- Fast Transcription API: phrase lists, 14-language multi-lingual transcription
- Azure Monitor Workbooks: Bicep support, RBAC specifics
- Power Platform Copilot: data residency (Norway/Europe → EU DB, Bing → USA)
- RAG security-rbac: 4-approach table (GA + 3 preview access control methods)
- IaC MLOps: Well-Architected OE:05 principles, Bicep/Terraform patterns
- Translator: image file batch translation Preview (JPEG/PNG/BMP/WebP)

All 106 files: Last updated 2026-04 | Verified: MCP 2026-04

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

plugins/ms-ai-architect/skills/ms-ai-engineering/references/rag-architecture/citation-tracking.md

@@ -1,6 +1,6 @@
 # Citation Tracking and Source Attribution
 
-**Last updated:** 2026-02
+**Last updated:** 2026-04 | Verified: MCP 2026-04
 **Status:** GA (classic RAG), Preview (agentic retrieval)
 **Category:** RAG Architecture & Semantic Search
 
@@ -292,3 +292,14 @@ result = groundedness_eval(
 - Norsk lovgivning (Forvaltningsloven, Offentleglova, Arkivloven)
 - Kostnadsoptimerings-anbefalinger
 - Modenhetsnivå-tabellen
+
+
+### Agentic Retrieval — Citation Tracking (oppdatert 2026-04)
+
+Azure AI Search agentic retrieval (preview) returnerer et tre-delt svar som gjør citation tracking robust:
+
+1. **Merged content** — samlet grounding data for LLM
+2. **Source references** — kildereferanser for inspeksjon og citation
+3. **Activity plan** — query execution-detaljer (subqueries, sources, parameters)
+
+Agentic retrieval bruker LLM til å rive ned komplekse queries til subqueries som kjøres parallelt, med semantisk reranking av hvert delresultat. Dette gir bedre grounding data enn klassisk RAG for komplekse spørsmål. Source references med full provenance tracking støtter transparenskrav i norsk offentlig sektor.