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>

skills/ms-ai-engineering/references/rag-architecture/rag-query-understanding.md

@@ -1,6 +1,6 @@
 # Query Understanding and Expansion
 
-**Last updated:** 2026-02
+**Last updated:** 2026-04 | Verified: MCP 2026-04
 **Status:** GA
 **Category:** RAG Architecture & Semantic Search
 
@@ -576,3 +576,22 @@ Multi-Query RAG med 3 varianter = ~3x søkekostnad + 1 LLM-kall for generering.
 - **ROI-tall (15-30% precision improvement):** Baseline — industry benchmarks, ikke Microsoft-spesifikk data
 
 **Totalt antall kilder:** 7 Microsoft Learn URLer (Verified) + 1 GitHub repo (Verified) = 8 kilder
+
+
+### Simple Query Syntax for RAG (oppdatert 2026-04)
+
+Azure AI Search simple query syntax er default parser for full-text søk i RAG:
+
+**Boolske operatorer (tegn-basert):**
+- `+` — AND (påkrevd term)
+- `|` — OR (alternativ term)
+- `-` — NOT (ekskluder term) — `searchMode=all` anbefales for presis NOT-atferd
+
+**Prefix queries:** `lingui*` — matcher "linguistic", "linguini" etc.
+
+**Phrase search:** `"eksakt frase"` — krever eksakt ordrekkefølge
+
+**Begrensninger:** Ingen fuzzy search, ingen suffix/infix wildcard (bruk full Lucene syntax for det).
+
+**Bruk i RAG query expansion:**
+Simple syntax egner seg for keyword-delen av hybrid queries. For agentic RAG bruker LLM query planning til å generere fokuserte subqueries som kombinerer full-text + vector search parallelt.