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/hybrid-search-configuration.md

@@ -1,6 +1,6 @@
 # Hybrid Search - Full-Text and Vector Combined
 
-**Last updated:** 2026-02
+**Last updated:** 2026-04 | Verified: MCP 2026-04
 **Status:** GA
 **Category:** RAG Architecture & Semantic Search
 
@@ -223,3 +223,27 @@ Bruk `debug: "vector"` eller `debug: "semantic"` i API-kallet for å pakke ut su
 ### Baseline (modellkunnskap)
 - Kostnadsoptimerings-tips basert på generell Azure-erfaring
 - Offentlig sektor-anbefalinger basert på norsk kontekst
+
+
+### Hybrid Search — Konfigurasjon og Tuning (oppdatert 2026-04)
+
+**Anbefalt startpunkt:** Balanced hybrid med `k=30-50`, `top=10-20`, semantic ranking etter relevans-test.
+
+**maxTextRecallSize (preview):** Kontrollerer BM25-bidrag til RRF
+- Default: 1000, Max: 10000
+- Reduser hvis vector dominerer; øk for store indekser der default ikke gir nok dekning
+- `countAndFacetMode: "countRetrievableResults"` scope-r teller til maxTextRecallSize-vinduet
+
+**Ytelsesmønstre:**
+- Recall-first: øk `maxTextRecallSize` gradvis
+- Precision-first: lav `k` og `top`, unngå unødvendig semantic ranker
+
+**Filter-moduser i hybrid:**
+- `preFilter` (default) — filtrerer FØR query, reduserer søkerom for begge subqueries
+- `postFilter` — filtrerer ETTER, men kan gi <50 docs til semantic ranker
+- `strictPostFilter` (preview) — strengeste modus, ikke anbefalt med semantic ranker
+- `filterOverride` (preview) — per-vectorQuery filter, overstyrer globalt filter
+
+**SDK-støtte:** Python (`azure-search-documents`), C# (`Azure.Search.Documents`), Java, JavaScript.
+
+**API-versjoner:** `2025-09-01` (stable), `2025-11-01-preview` (maxTextRecallSize, filterOverride, etc.)