fix(ms-ai-architect): Foundry URL-navnerom-migrering (ai-foundry → foundry/foundry-classic, 141 filer)

Task #5 del 1/3 (URL-migrering). Verifiseringen motbeviste STATE.md-premisset om ren prefix-swap: rebrand er per-URL, ikke mekanisk. En blind sed ai-foundry→foundry ville lagd 56 nye 404-er (classic-stiene finnes ikke under nytt foundry/-prefiks — bekreftet empirisk). Metode: resolverte alle 237 unike KB-URLer mot live redirects (curl -L), bygde full-URL→full-URL-mapping fra faktisk url_effective. Bevarer locale-form, query (?view=) og #fragment per lenke. - 231 navnerom-erstatninger over 141 filer (408 forekomster): - 161 → azure/foundry/ (98 ren prefix-swap + 10 sti-reorg + reorg-tilfeller) - 69 → azure/foundry-classic/ (eldre hub-spor: assistants, hub-DR, on-your-data; faktisk redirect-mål per operatorvalg) - 1 → azure/foundry-local/ - 2 døde lenker (404) fikset til verifiserte mål: - agent-service → azure/foundry/agents/overview - concepts/evaluation-evaluators/ → azure/foundry/how-to/evaluate-generative-ai-app - 5 path-/display-referanser (uten https://, i backticks/lenketekst) rettet manuelt. - 6 slug-baserte ai-foundry-treff urørt (scope-grense): managed-grafana-dashboard, security-baseline, power-platform prompt-builder, architecture baseline-chat (sistnevnte slug-rebrand i annet navnerom — mulig fremtidig funn). - Parkert til task #5 del 2/3: Norway East GPT-5-datasuverenitet-fiks + modellkatalog-utvidelse (5.3/5.4/5.5, gpt-oss, sora-2). Verifisert: 0 gjenværende azure/ai-foundry/-navnerom i skills/. validate-plugin.sh 219 PASS. test-kb-integrity.sh 117/117 passed. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01REiKFhP4w6xGXXqWKpPCJJ
2026-06-18 13:37:06 +02:00 · 2026-06-18 13:37:06 +02:00 · dd1036ab8a
commit dd1036ab8a
parent 84e3cfaa03
141 changed files with 399 additions and 399 deletions
--- a/skills/ms-ai-engineering/references/agent-orchestration/agent-autonomy-and-control-governance.md
+++ b/skills/ms-ai-engineering/references/agent-orchestration/agent-autonomy-and-control-governance.md
@ -390,7 +390,7 @@ workflow = (
 3. [Process to build agents across your organization](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/ai-agents/build-secure-process)
   Confidence: High — Tool boundaries, human-in-the-loop mandates, compliance frameworks

-4. [Guardrails and controls overview in Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/guardrails/guardrails-overview)
+4. [Guardrails and controls overview in Microsoft Foundry](https://learn.microsoft.com/en-us/azure/foundry/guardrails/guardrails-overview)
   Confidence: High — Intervention points, risk categories, agent vs. model guardrails

 5. [Secure AI agents at scale using Microsoft Agent 365](https://learn.microsoft.com/en-us/security/security-for-ai/agent-365-security)
--- a/skills/ms-ai-engineering/references/agent-orchestration/agent-evaluation-testing-frameworks.md
+++ b/skills/ms-ai-engineering/references/agent-orchestration/agent-evaluation-testing-frameworks.md
@ -482,19 +482,19 @@ results = mlflow.genai.evaluate(
 ### Microsoft Learn (MCP-verified)

 1. **Evaluate your AI agents (preview)**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/agent-evaluate-sdk?view=foundry-classic
+   https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/agent-evaluate-sdk?view=foundry-classic
   *Confidence: Verified* — Hovedreferanse for Azure AI Evaluation SDK, evaluator types, model support

 2. **Continuously evaluate your AI agents (preview)**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/continuous-evaluation-agents?view=foundry-classic
+   https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/continuous-evaluation-agents?view=foundry-classic
   *Confidence: Verified* — Continuous evaluation setup, sampling configuration, Application Insights integration

 3. **Run evaluations in the cloud by using the Microsoft Foundry SDK**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/cloud-evaluation?view=foundry-classic
+   https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/cloud-evaluation?view=foundry-classic
   *Confidence: Verified* — Cloud batch evaluation, CI/CD integration, dataset formats

 4. **Tutorial: Idea to prototype - Build and evaluate an enterprise agent**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/tutorials/developer-journey-idea-to-prototype?view=foundry
+   https://learn.microsoft.com/en-us/azure/foundry/tutorials/developer-journey-idea-to-prototype?view=foundry
   *Confidence: Verified* — End-to-end tutorial med cloud evaluation, built-in evaluators

 5. **Test and evaluate AI workloads on Azure (Well-Architected Framework)**
@ -502,15 +502,15 @@ results = mlflow.genai.evaluate(
   *Confidence: Verified* — Agentic workflow testing strategy, tool call validation, security testing

 6. **Observability in generative AI**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability
+   https://learn.microsoft.com/en-us/azure/foundry/concepts/observability
   *Confidence: Verified* — Built-in evaluators list, GenAIOps evaluation stages, simulators

 7. **What are hosted agents? (Evaluate and test hosted agents)**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/agents/concepts/hosted-agents?view=foundry#evaluate-and-test-hosted-agents
+   https://learn.microsoft.com/en-us/azure/foundry/agents/concepts/hosted-agents?view=foundry#evaluate-and-test-hosted-agents
   *Confidence: Verified* — Hosted agent evaluation best practices, test dataset creation

 8. **Agent evaluators**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/evaluation-evaluators/agent-evaluators?view=foundry
+   https://learn.microsoft.com/en-us/azure/foundry/concepts/evaluation-evaluators/agent-evaluators?view=foundry
   *Confidence: Verified* — Agent-specific evaluator details (Intent Resolution, Task Adherence, Tool Call Accuracy)

 9. **Evaluate and monitor AI agents (MLflow 3 on Databricks)**
--- a/skills/ms-ai-engineering/references/agent-orchestration/agent-memory-and-context-management.md
+++ b/skills/ms-ai-engineering/references/agent-orchestration/agent-memory-and-context-management.md
@ -461,7 +461,7 @@ Gir data lineage tracking og governance-enforcement.
   Confidence: ✅ Verified (Mem0Provider, WhiteboardProvider documentation)

 2. **Foundry Agent Service Memory (preview)**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/agents/concepts/what-is-memory?view=foundry
+   https://learn.microsoft.com/en-us/azure/foundry/agents/concepts/what-is-memory?view=foundry
   Confidence: ✅ Verified (Managed Memory Store, extraction/consolidation/retrieval phases)

 3. **Agent Framework Chat History Providers**
@ -485,7 +485,7 @@ Gir data lineage tracking og governance-enforcement.
   Confidence: ✅ Verified (Hierarchical memory: knowledge, long-term, short-term)

 8. **Azure OpenAI Web App Chat History (Cosmos DB)**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/use-web-app
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/use-web-app
   Confidence: ✅ Verified (Cosmos DB enablement for chat history)

 ### Konfidensnivå per seksjon
@ -505,13 +505,13 @@ Gir data lineage tracking og governance-enforcement.
 ### Unique Microsoft Learn URLs accessed

 1. `/semantic-kernel/frameworks/agent/agent-memory`
-2. `/azure/ai-foundry/agents/concepts/what-is-memory`
+2. `/azure/foundry/agents/concepts/what-is-memory`
 3. `/agent-framework/integrations/overview`
 4. `/azure/copilot/bring-your-own-storage`
 5. `/semantic-kernel/concepts/vector-store-connectors/memory-stores`
 6. `/agent-framework/tutorials/agents/multi-turn-conversation`
 7. `/azure/cloud-adoption-framework/ai-agents/build-secure-process`
-8. `/azure/ai-foundry/openai/how-to/use-web-app`
+8. `/azure/foundry-classic/openai/how-to/use-web-app`

 **Total unique sources**: 8 Microsoft Learn URLs
 **MCP calls**: 6 (3x microsoft_docs_search, 2x microsoft_docs_fetch, 1x microsoft_code_sample_search)
--- a/skills/ms-ai-engineering/references/agent-orchestration/agent-to-agent-a2a-protocol.md
+++ b/skills/ms-ai-engineering/references/agent-orchestration/agent-to-agent-a2a-protocol.md
@ -654,11 +654,11 @@ app.MapA2A(agent, "/a2a/my-agent", agentCard: new()
 ### Microsoft Learn (Verified)

 1. **Foundry Agent Service — A2A Tool**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools/agent-to-agent
+   - https://learn.microsoft.com/azure/foundry/agents/how-to/tools/agent-to-agent
   - Confidence: **Verified** (offisiell guide, preview, februar 2026)

 2. **A2A Authentication in Foundry**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/concepts/agent-to-agent-authentication
+   - https://learn.microsoft.com/azure/foundry/agents/concepts/agent-to-agent-authentication
   - Confidence: **Verified** (offisiell auth-guide, februar 2026)

 3. **Copilot Studio — Connect A2A Agent**
--- a/skills/ms-ai-engineering/references/agent-orchestration/computer-using-agents-cua.md
+++ b/skills/ms-ai-engineering/references/agent-orchestration/computer-using-agents-cua.md
@ -482,7 +482,7 @@ Kostnader basert på:
 ### Microsoft Learn (Verified)

 1. **Foundry Agent Service Computer Use Tool**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools/computer-use
+   - https://learn.microsoft.com/azure/foundry/agents/how-to/tools/computer-use
   - Confidence: **Verified** (offisiell Foundry-dokumentasjon, sep 2025)

 2. **Automate web and desktop apps with computer use — Copilot Studio**
@ -494,7 +494,7 @@ Kostnader basert på:
   - Confidence: **Verified** (Copilot Studio docs, 2025)

 4. **Browser Automation (preview) — Foundry Agent Service**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools/browser-automation
+   - https://learn.microsoft.com/azure/foundry/agents/how-to/tools/browser-automation
   - Confidence: **Verified** (aug 2025, public preview)

 5. **CUA vs RPA — Use agent tools to extend agents**
--- a/skills/ms-ai-engineering/references/agent-orchestration/foundry-agent-service-ga.md
+++ b/skills/ms-ai-engineering/references/agent-orchestration/foundry-agent-service-ga.md
@ -327,7 +327,7 @@ Foundry Agent Service er tilgjengelig i følgende Azure-regioner (per februar 20
 - Code Interpreter er ikke tilgjengelig i alle regioner

 **Sjekk regional verktøytilgjengelighet:**
-[learn.microsoft.com/azure/ai-foundry/agents/concepts/tool-best-practice#tool-support-by-region-and-model](https://learn.microsoft.com/azure/ai-foundry/agents/concepts/tool-best-practice?view=foundry#tool-support-by-region-and-model)
+[learn.microsoft.com/azure/foundry/agents/concepts/tool-best-practice#tool-support-by-region-and-model](https://learn.microsoft.com/azure/foundry/agents/concepts/tool-best-practice?view=foundry#tool-support-by-region-and-model)

 ## Enterprise-sikkerhet og governance

@ -475,27 +475,27 @@ Rate limiting skjer på modell-deployment-nivå, ikke Agent Service-nivå. Se Az
 ### Microsoft Learn (Verified)

 1. **What is Foundry Agent Service?**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/overview?view=foundry-classic
+   - https://learn.microsoft.com/azure/foundry/agents/overview?view=foundry-classic
   - Confidence: **Verified** (offisiell oversikt, GA-dokumentasjon)

 2. **What's new in Foundry Agent Service (GA mai 2025)**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/whats-new?view=foundry-classic
+   - https://learn.microsoft.com/azure/foundry-classic/agents/whats-new?view=foundry-classic
   - Confidence: **Verified** (changelog, mai–juni 2025)

 3. **Connected Agents**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/connected-agents?view=foundry-classic
+   - https://learn.microsoft.com/azure/foundry-classic/agents/how-to/connected-agents?view=foundry-classic
   - Confidence: **Verified** (multi-agent SDK guide og eksempler)

 4. **Foundry Agent Service limits, quotas, and regional support**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/concepts/limits-quotas-regions?view=foundry
+   - https://learn.microsoft.com/azure/foundry/agents/concepts/limits-quotas-regions?view=foundry
   - Confidence: **Verified** (komplett region- og grense-tabell)

 5. **MCP tool — Foundry Agent Service**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools-classic/model-context-protocol-samples?view=foundry-classic
+   - https://learn.microsoft.com/azure/foundry-classic/agents/how-to/tools-classic/model-context-protocol-samples?view=foundry-classic
   - Confidence: **Verified** (C# og Python code samples)

 6. **Threads, runs, and messages**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/concepts/threads-runs-messages?view=foundry-classic
+   - https://learn.microsoft.com/azure/foundry-classic/agents/concepts/threads-runs-messages?view=foundry-classic
   - Confidence: **Verified** (kjernekonsept-dokumentasjon)

 7. **AzureAIAgent Foundry GA Migration Guide (SK Python)**
@ -503,11 +503,11 @@ Rate limiting skjer på modell-deployment-nivå, ikke Agent Service-nivå. Se Az
   - Confidence: **Verified** (breaking changes og migrasjonsguide)

 8. **Transparency Note for Azure Agent Service**
-   - https://learn.microsoft.com/azure/ai-foundry/responsible-ai/agents/transparency-note?view=foundry-classic
+   - https://learn.microsoft.com/azure/foundry/responsible-ai/agents/transparency-note?view=foundry-classic
   - Confidence: **Verified** (ansvarlig AI-rammeverk)

 9. **Foundry Agent Service FAQ (prising)**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/faq?view=foundry-classic
+   - https://learn.microsoft.com/azure/foundry/agents/faq?view=foundry-classic
   - Confidence: **Verified** (offisiell prisingsforklaring)

 ### Confidence per seksjon
--- a/skills/ms-ai-engineering/references/agent-orchestration/foundry-workflows-visual-orchestration.md
+++ b/skills/ms-ai-engineering/references/agent-orchestration/foundry-workflows-visual-orchestration.md
@ -583,19 +583,19 @@ Foundry Workflows' visuelle designer gir offentlig sektor-organisasjoner en unik
 ### Microsoft Learn (Verified)

 1. **Build a workflow in Microsoft Foundry**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/concepts/workflow?view=foundry
+   - https://learn.microsoft.com/azure/foundry/agents/concepts/workflow?view=foundry
   - Confidence: **Verified** (offisiell workflow-guide, Foundry new portal)

 2. **Agent development lifecycle**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/concepts/development-lifecycle?view=foundry
+   - https://learn.microsoft.com/azure/foundry/agents/concepts/development-lifecycle?view=foundry
   - Confidence: **Verified** (versjonering, publisering, livssyklus, januar 2025)

 3. **Publish and share agents in Microsoft Foundry**
-   - https://learn.microsoft.com/azure/ai-foundry/agents/how-to/publish-agent?view=foundry
+   - https://learn.microsoft.com/azure/foundry/agents/how-to/agent-applications?view=foundry
   - Confidence: **Verified** (Agent Application deployment, API-kall, RBAC)

 4. **Monitor agents with the Agent Monitoring Dashboard**
-   - https://learn.microsoft.com/azure/ai-foundry/observability/how-to/how-to-monitor-agents-dashboard?view=foundry
+   - https://learn.microsoft.com/azure/foundry/observability/how-to/how-to-monitor-agents-dashboard?view=foundry
   - Confidence: **Verified** (token usage, latency, success rate, evaluators)

 5. **Declarative Workflows — Overview (Agent Framework)**
@ -607,7 +607,7 @@ Foundry Workflows' visuelle designer gir offentlig sektor-organisasjoner en unik
   - Confidence: **Verified** (HITL-mønster, pause og resume, compliance)

 7. **Transparency Note for Azure Agent Service**
-   - https://learn.microsoft.com/azure/ai-foundry/responsible-ai/agents/transparency-note?view=foundry-classic
+   - https://learn.microsoft.com/azure/foundry/responsible-ai/agents/transparency-note?view=foundry-classic
   - Confidence: **Verified** (Foundry Workflows capabilities, visioning, governance)

 ### Microsoft Dev Blog (Verified)
--- a/skills/ms-ai-engineering/references/agent-orchestration/tool-use-and-function-calling-patterns.md
+++ b/skills/ms-ai-engineering/references/agent-orchestration/tool-use-and-function-calling-patterns.md
@ -448,12 +448,12 @@ def update_citizen_record(ssn: str, field: str, value: str) -> str:

 ### Microsoft Learn-kilder (Verified via MCP)

-1. [Azure OpenAI Function Calling](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/function-calling) — **Verified 2026-02**
+1. [Azure OpenAI Function Calling](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/function-calling) — **Verified 2026-02**
 2. [Semantic Kernel Agent Functions](https://learn.microsoft.com/en-us/semantic-kernel/frameworks/agent/agent-functions) — **Verified 2026-02**
 3. [Agent Framework - Agent as Function Tool](https://learn.microsoft.com/en-us/agent-framework/tutorials/agents/agent-as-function-tool) — **Verified 2026-02**
 4. [AG-UI Backend Tool Rendering](https://learn.microsoft.com/en-us/agent-framework/integrations/ag-ui/backend-tool-rendering) — **Verified (MCP 2026-04)** — AIFunctionFactory.Create() med serializerOptions for komplekse typer (C#), @tool decorator med Annotated/Field (Python), TOOL_CALL_START/ARGS/END/RESULT events, FunctionCallContent/.Arguments og FunctionResultContent/.Result (C#), klasse-baserte tools-moenster (Python)
-5. [Azure OpenAI Assistants Function Calling](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/assistant-functions) — **Verified 2026-02**
-6. [Structured Outputs](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/structured-outputs) — **Verified 2026-02**
+5. [Azure OpenAI Assistants Function Calling](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/assistant-functions) — **Verified 2026-02**
+6. [Structured Outputs](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/structured-outputs) — **Verified 2026-02**

 ### Konfidensnivå per seksjon

--- a/skills/ms-ai-engineering/references/api-management/multi-region-ai-gateway-design.md
+++ b/skills/ms-ai-engineering/references/api-management/multi-region-ai-gateway-design.md
@ -423,7 +423,7 @@ Hver region krever eget VNet med nødvendige NSG-regler:
 - [Use a gateway in front of multiple Azure OpenAI deployments or instances](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-multi-backend) — Arkitekturmønstre for AI gateway
 - [AI gateway in Azure API Management](https://learn.microsoft.com/en-us/azure/api-management/genai-gateway-capabilities) — Oversikt over AI gateway-kapabiliteter
 - [Access Azure OpenAI through a gateway](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-guide) — Well-Architected Framework-veiledning
- [Azure OpenAI deployment types](https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/concepts/deployment-types) — Deployment types og data residency
+- [Azure OpenAI deployment types](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/deployment-types) — Deployment types og data residency

 ---

--- a/skills/ms-ai-engineering/references/api-management/streaming-support-apim.md
+++ b/skills/ms-ai-engineering/references/api-management/streaming-support-apim.md
@ -505,7 +505,7 @@ For ikke-streaming requests, bruk standard `llm-emit-token-metric` i outbound:

 - [Configure API for server-sent events](https://learn.microsoft.com/en-us/azure/api-management/how-to-server-sent-events) — Offisiell SSE-guide for APIM
 - [AI gateway in Azure API Management](https://learn.microsoft.com/en-us/azure/api-management/genai-gateway-capabilities) — AI gateway oversikt
- [Azure OpenAI REST API reference - Chat Completions](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/reference#chat-completions) — Stream-parameter dokumentasjon
+- [Azure OpenAI REST API reference - Chat Completions](https://learn.microsoft.com/en-us/azure/foundry/openai/reference#chat-completions) — Stream-parameter dokumentasjon
 - [forward-request policy](https://learn.microsoft.com/en-us/azure/api-management/forward-request-policy) — Policy-referanse for forwarding
 - [Log token usage, prompts, and completions](https://learn.microsoft.com/en-us/azure/api-management/api-management-howto-llm-logs) — LLM-logging i APIM

--- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-api-best-practices.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-api-best-practices.md
@ -709,11 +709,11 @@ AzureDiagnostics
   - Confidence: **Verified** (MCP fetch)

 4. **Get started using provisioned deployments on Azure OpenAI**
-   - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-get-started
+   - URL: https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/provisioned-get-started
   - Confidence: **Verified** (MCP fetch)

 5. **Getting started with Azure OpenAI batch deployments**
-   - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch
+   - URL: https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch
   - Confidence: **Verified** (MCP search)

 6. **Azure AI services authentication and authorization using .NET**
--- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-cost-optimization.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-cost-optimization.md
@ -331,15 +331,15 @@ PTU er en kapasitetsbasert prismodell for Azure OpenAI, primært for produksjons
   *Sist sjekket: 2026-02*

 2. **Provisioned Throughput Concepts**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/provisioned-throughput
+   https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput
   *Sist sjekket: 2026-02*

 3. **Provisioned Throughput Onboarding (PTU Cost Management)**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding
+   https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput-billing
   *Sist sjekket: 2026-02*

 4. **Plan and Manage Costs for Azure OpenAI**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs
+   https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs
   *Sist sjekket: 2026-02*

 5. **Govern AI Costs (Cloud Adoption Framework)**
@ -374,7 +374,7 @@ PTU er en kapasitetsbasert prismodell for Azure OpenAI, primært for produksjons
 - microsoft_docs_search: "Azure AI Services reserved capacity commitment tier"
 - microsoft_docs_search: "Azure AI Services budget management cost estimation"
 - microsoft_docs_fetch: `/azure/ai-services/commitment-tier`
- microsoft_docs_fetch: `/azure/ai-foundry/openai/how-to/manage-costs`
+- microsoft_docs_fetch: `/azure/foundry/concepts/manage-costs`
 - microsoft_docs_fetch: `/azure/cloud-adoption-framework/scenarios/ai/platform/governance`
 - microsoft_docs_search: "Azure OpenAI provisioned throughput PTU cost optimization"

--- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-enterprise-architecture.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-enterprise-architecture.md
@ -545,7 +545,7 @@ TOTAL: ~46 700 NOK/måned (høyere cost, men forutsigbar)

 **Microsoft Learn Documentation (offisiell, 2026-02):**
 1. [AI Ready - Cloud Adoption Framework](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/ready)
-2. [BCDR for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/business-continuity-disaster-recovery)
+2. [BCDR for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/high-availability-resiliency)
 3. [Baseline Foundry Chat Architecture (Foundry Agent Service + Microsoft Agent Framework)](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/architecture/baseline-microsoft-foundry-chat) — Verified (MCP 2026-04)
 4. [Azure API Management - AI Gateway Capabilities](https://learn.microsoft.com/en-us/azure/api-management/genai-gateway-capabilities)
 5. [Reliability in Azure AI Search](https://learn.microsoft.com/en-us/azure/reliability/reliability-ai-search)
@ -559,7 +559,7 @@ TOTAL: ~46 700 NOK/måned (høyere cost, men forutsigbar)

 **Verifikasjon:**
 - ✅ Alle arkitekturdiagrammer basert på Microsoft offisiell dokumentasjon
- ✅ Deployment-typer (Global/Data Zone/Regional/PTU) verifisert mot [Deployment Types](https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/concepts/deployment-types)
+- ✅ Deployment-typer (Global/Data Zone/Regional/PTU) verifisert mot [Deployment Types](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/deployment-types)
 - ✅ APIM circuit breaker pattern bekreftet i [Backends Documentation](https://learn.microsoft.com/en-us/azure/api-management/backends)
 - ✅ Zone redundancy requirements verifisert mot [Availability Zones Overview](https://learn.microsoft.com/en-us/azure/reliability/availability-zones-overview)

--- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-monitoring-logging.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-monitoring-logging.md
@ -544,7 +544,7 @@ Hvis du bruker ITSM-integrasjoner (ServiceNow, etc.) via Action Groups, kan det

 **Verified (MCP-research, januar 2026):**
 - [Enable diagnostic logging for Foundry Tools](https://learn.microsoft.com/en-us/azure/ai-services/diagnostic-logging) – Offisiell guide, sist oppdatert 2024
- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) – Kusto queries, diagnostic settings, dashboards
+- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) – Kusto queries, diagnostic settings, dashboards
 - [Introduction to Application Insights](https://learn.microsoft.com/en-us/azure/azure-monitor/app/app-insights-overview) – OpenTelemetry-basert APM
 - [Monitor Azure AI services (Training module)](https://learn.microsoft.com/en-us/training/modules/monitor-ai-services/) – Microsoft Learn offisiell kurs

--- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-networking-security.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-networking-security.md
@ -591,8 +591,8 @@ Test-NetConnection -ComputerName 10.0.2.5 -Port 443
 **Verified (MCP microsoft-learn, 2026-02):**
 - [Configure Foundry Tools virtual networks](https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-virtual-networks) - Hovedkilde for VNet-konfigurasjon, service endpoints, IP-regler, private endpoints
 - [Configure secure networking for Azure AI platform services](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/platform/networking) - Arkitektur-guide fra Cloud Adoption Framework
- [Configure Azure OpenAI networking](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/network) - Private endpoint oppsett for Azure OpenAI
- [Network and access configuration for Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/on-your-data-configuration) - Trusted services bypass, managed identity setup
+- [Configure Azure OpenAI networking](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/network) - Private endpoint oppsett for Azure OpenAI
+- [Network and access configuration for Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/on-your-data-configuration) - Trusted services bypass, managed identity setup
 - [Azure security baseline for Azure AI services](https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/cognitive-services-security-baseline) - NSG-støtte (ikke støttet), private link (støttet), disable public access
 - [Create a private endpoint for a secure connection to Azure AI Search](https://learn.microsoft.com/en-us/azure/search/service-create-private-endpoint) - Shared private link-mønster

--- a/skills/ms-ai-engineering/references/azure-ai-services/ai-services-vs-foundry-tools-selection.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/ai-services-vs-foundry-tools-selection.md
@ -675,7 +675,7 @@ START: Hvilken AI-kapabilitet trenger du?
   Dato: 2026-02 (verifisert)

 3. **Choose an Azure resource type for Foundry**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/resource-types
+   https://learn.microsoft.com/en-us/azure/foundry-classic/concepts/resource-types
   Dato: 2026-02 (verifisert)

 4. **Choose the right Foundry tool for document processing**
@ -683,11 +683,11 @@ START: Hvilken AI-kapabilitet trenger du?
   Dato: 2026-02 (verifisert)

 5. **What is Foundry Agent Service?**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/agents/overview
+   https://learn.microsoft.com/en-us/azure/foundry/agents/overview
   Dato: 2026-02 (verifisert)

 6. **Plan and manage costs for Microsoft Foundry**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/manage-costs
+   https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs
   Dato: 2026-02 (verifisert)

 7. **Azure OpenAI pricing page**
--- a/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-image-analysis.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-image-analysis.md
@ -360,7 +360,7 @@ Azure AI Vision er en **Azure resource** som faktureres direkte via Azure-abonne
 3. [Object detection (version 4.0)](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-object-detection-40) - Bounding box-basert objektdeteksjon
 4. [Image tagging with Image Analysis version 4.0](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-tag-images-40) - Tagging av tusenvis av objekter
 5. [What's new in Azure Vision in Foundry Tools](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/whats-new) - Florence integration (mars 2023), GA-lansering (november 2023)
-6. [Transparency note: Image Analysis](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/computer-vision/image-analysis-transparency-note) - Florence foundation model, bounding boxes, confidence scores
+6. [Transparency note: Image Analysis](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/computer-vision/image-analysis-transparency-note) - Florence foundation model, bounding boxes, confidence scores
 7. [Call the Image Analysis 4.0 Analyze API (Python)](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/call-analyze-image-40?pivots=programming-language-python) - SDK implementation
 8. [Azure Image Analysis client library for Python](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-vision-imageanalysis-readme) - Visual features, gender-neutral captions

--- a/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-ocr-processing.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/azure-ai-vision-ocr-processing.md
@ -334,9 +334,9 @@ Kombiner OCR med LLM for intelligent dokumentforståelse:
 3. **Call Azure Vision v3.2 GA Read API**: https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/call-read-api
 4. **Quickstart: Azure Vision v3.2 GA Read (Python)**: https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/client-library
 5. **Quickstart: Azure Vision v3.2 GA Read (REST API)**: https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/client-library
-6. **Data, privacy, and security for OCR**: https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/computer-vision/ocr-data-privacy-security
-7. **Transparency note and use cases for OCR**: https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/computer-vision/ocr-transparency-note
-8. **Capabilities and limitations of OCR**: https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/computer-vision/ocr-characteristics-and-limitations
+6. **Data, privacy, and security for OCR**: https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/computer-vision/ocr-data-privacy-security
+7. **Transparency note and use cases for OCR**: https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/computer-vision/ocr-transparency-note
+8. **Capabilities and limitations of OCR**: https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/computer-vision/ocr-characteristics-and-limitations
 9. **Image Analysis cognitive skill (AI Search)**: https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-image-analysis
 10. **Tutorial: Vision with Azure AI services (Synapse)**: https://learn.microsoft.com/en-us/azure/synapse-analytics/machine-learning/tutorial-computer-vision-use-mmlspark
 11. **Azure Vision Image Analysis Python SDK**: https://learn.microsoft.com/en-us/python/api/overview/azure/ai-vision-imageanalysis-readme
--- a/skills/ms-ai-engineering/references/azure-ai-services/content-understanding-multimodal-analysis.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/content-understanding-multimodal-analysis.md
@ -576,7 +576,7 @@ Content Understanding er en **Azure Foundry Tools** tjeneste, inkludert i:
 | Multimodal search (AI Search integration) | https://learn.microsoft.com/en-us/azure/search/multimodal-search-overview | Verified (Feb 2026) |
 | Azure AI Video Indexer insights overview | https://learn.microsoft.com/en-us/azure/azure-video-indexer/insights-overview | Verified (Feb 2026) |
 | Python SDK (ContentUnderstandingClient) | https://learn.microsoft.com/en-us/python/api/overview/azure/ai-contentunderstanding-readme | Verified (Feb 2026) |
-| Data privacy and security | https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/content-understanding/data-privacy | Verified (Feb 2026) |
+| Data privacy and security | https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/content-understanding/data-privacy | Verified (Feb 2026) |

 ### Baseline (modellkunnskap)

--- a/skills/ms-ai-engineering/references/azure-ai-services/speech-services-speaker-recognition.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/speech-services-speaker-recognition.md
@ -474,7 +474,7 @@ Før du anbefaler Speaker Recognition:
   - Coverage: Feature overview, verification vs. identification, use cases

 3. **Data Privacy and Security for Text-to-Speech**
-   - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/speech-service/text-to-speech/data-privacy-security
+   - URL: https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/speech-service/text-to-speech/data-privacy-security
   - Confidence: **Verified** (MCP fetch 2026-02-03)
   - Coverage: Speaker Verification for voice talent consent, voice signature processing, DPA compliance

--- a/skills/ms-ai-engineering/references/azure-ai-services/speech-services-text-to-speech.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/speech-services-text-to-speech.md
@ -495,7 +495,7 @@ Billable characters: `Hello, world!` = 13 tegn (ikke `<speak>` eller `<voice>`)
 | Customize voice and sound with SSML | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-synthesis-markup-voice |
 | How to synthesize speech from text | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-services/speech-service/how-to-speech-synthesis |
 | Text-to-Speech FAQ | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-services/speech-service/faq-tts |
-| Transparency note for TTS | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/speech-service/text-to-speech/transparency-note |
+| Transparency note for TTS | ✅ Verified | https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/speech-service/text-to-speech/transparency-note |
 | Language support | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts |
 | Speech service pricing | ✅ Verified | https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/ |
 | Batch synthesis API | ✅ Verified | https://learn.microsoft.com/en-us/azure/ai-services/speech-service/batch-synthesis |
--- a/skills/ms-ai-engineering/references/azure-ai-services/translator-document-translation.md
+++ b/skills/ms-ai-engineering/references/azure-ai-services/translator-document-translation.md
@ -329,7 +329,7 @@ General translation  Domain-specific terms
 - Start med **Foundry (classic) portal** for manuell testing
 - Bruk **Single-file API** for prototyping (enklere enn Blob Storage)
 - Test med maksimalt 3 språkpar først
- Les [Transparency Note](https://learn.microsoft.com/azure/ai-foundry/responsible-ai/translator/transparency-note) for å forstå begrensninger
+- Les [Transparency Note](https://learn.microsoft.com/azure/foundry/responsible-ai/translator/transparency-note) for å forstå begrensninger

 **Middels (har brukt Text Translation API):**
 - Migrer til **Batch Translation** for volum > 50 filer/dag
@ -369,7 +369,7 @@ General translation  Domain-specific terms
   *Confidence: Verified (2026-02)* — Rate limits, request size limits

 6. **Translator Transparency Note**
-   https://learn.microsoft.com/azure/ai-foundry/responsible-ai/translator/transparency-note
+   https://learn.microsoft.com/azure/foundry/responsible-ai/translator/transparency-note
   *Confidence: Verified (2026-02)* — AI-begrensninger, data privacy, responsible AI

 ### Konfidensnivå per seksjon
--- a/skills/ms-ai-engineering/references/data-engineering/data-anonymization-privacy.md
+++ b/skills/ms-ai-engineering/references/data-engineering/data-anonymization-privacy.md
@ -549,11 +549,11 @@ def privacy_check_before_deployment(model_artifacts_path: str) -> dict:
 ## Referanser

 - [What is Azure Language PII detection?](https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/overview) -- PII-deteksjon og maskering
- [PII filter in Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-personal-information) -- PII-filtrering for LLM-er
+- [PII filter in Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-personal-information) -- PII-filtrering for LLM-er
 - [Responsible AI - Privacy and security](https://learn.microsoft.com/en-us/azure/machine-learning/concept-responsible-ai) -- SmartNoise og Counterfit
 - [Data privacy for cloud-scale analytics](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/cloud-scale-analytics/secure-data-privacy) -- Dataklassifisering og konfidensialitetsskjema
 - [PII entity categories](https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/concepts/entity-categories) -- Alle stottede PII-kategorier
- [Transparency note for PII](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/language-service/transparency-note-personally-identifiable-information) -- Bruksomrader og begrensninger
+- [Transparency note for PII](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/language-service/transparency-note-personally-identifiable-information) -- Bruksomrader og begrensninger
 - [Data governance with Microsoft Purview](https://learn.microsoft.com/en-us/purview/data-governance-master-data-management) -- Purview for dataklassifisering

 ---
--- a/skills/ms-ai-engineering/references/data-engineering/data-quality-ai-frameworks.md
+++ b/skills/ms-ai-engineering/references/data-engineering/data-quality-ai-frameworks.md
@ -550,7 +550,7 @@ def trigger_purview_profiling(data_asset_id, connection_id):
 ### Code samples (Microsoft Learn)

 - **Azure ML fine-tuning job with validation data**
-  https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/fine-tune-serverless
+  https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/fine-tune-serverless
  Python SDK sample for creating validation dataset asset.

 - **AutoML training/validation MLTable inputs**
--- a/skills/ms-ai-engineering/references/data-engineering/synthetic-data-generation.md
+++ b/skills/ms-ai-engineering/references/data-engineering/synthetic-data-generation.md
@ -408,11 +408,11 @@ for metric, result in validation.items():

 ## Referanser

- [Generate synthetic and simulated data for evaluation](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/simulator-interaction-data) -- Azure AI Evaluation Simulator
- [Generate synthetic data for fine-tuning in Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/fine-tuning/data-generation) -- Foundry syntetisk data UI
+- [Generate synthetic and simulated data for evaluation](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/simulator-interaction-data) -- Azure AI Evaluation Simulator
+- [Generate synthetic data for fine-tuning in Microsoft Foundry](https://learn.microsoft.com/en-us/azure/foundry/fine-tuning/data-generation) -- Foundry syntetisk data UI
 - [Design training data for AI workloads on Azure](https://learn.microsoft.com/en-us/azure/well-architected/ai/training-data-design) -- Well-Architected Framework for treningsdata
 - [Azure OpenAI for big data](https://learn.microsoft.com/en-us/fabric/data-science/open-ai) -- SynapseML + OpenAI på Fabric
- [Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data) -- RAG for datagenerering
+- [Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data) -- RAG for datagenerering

 ---

--- a/skills/ms-ai-engineering/references/mlops-genaiops/feedback-loops-continuous-improvement.md
+++ b/skills/ms-ai-engineering/references/mlops-genaiops/feedback-loops-continuous-improvement.md
@ -715,7 +715,7 @@ mlflow.log_param("user_id_hash", user_id_hash)  # Logged
 1. [MLflow for GenAI Apps and Agents - Continuous Improvement Cycle](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/overview/) (Verified MCP 2026-04 — updated 10-step cycle; new: Trace UI for pattern identification, evaluation harness, version/prompt management tracking)
 2. [Machine Learning Operations v2 - Monitoring & Feedback](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/machine-learning-operations-v2)
 3. [Generative AI App Developer Workflow - Production Monitoring](https://learn.microsoft.com/en-us/azure/databricks/generative-ai/tutorials/ai-cookbook/genai-developer-workflow)
-4. [Azure AI Foundry - Observability in Generative AI](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability)
+4. [Azure AI Foundry - Observability in Generative AI](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability)
 5. [MLOps and GenAIOps for AI Workloads - Model Maintenance](https://learn.microsoft.com/en-us/azure/well-architected/ai/mlops-genaiops#model-maintenance)
 6. [AI Builder - Continuously Improve Your Model (Feedback Loop)](https://learn.microsoft.com/en-us/ai-builder/feedback-loop)

--- a/skills/ms-ai-engineering/references/mlops-genaiops/genaiops-llm-specific-practices.md
+++ b/skills/ms-ai-engineering/references/mlops-genaiops/genaiops-llm-specific-practices.md
@ -350,7 +350,7 @@ MLflow Tracing provides end-to-end observability for GenAI applications:
 8. [Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-evaluation-readme)
 9. [Mosaic AI capabilities for GenAI](https://learn.microsoft.com/en-us/azure/databricks/generative-ai/guide/mosaic-ai-gen-ai-capabilities)
 10. [MLflow Prompt Registry](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/)
-11. [Azure AI Foundry monitoring](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/monitor-quality-safety)
+11. [Azure AI Foundry monitoring](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/monitor-quality-safety)
 12. [MLflow Tracing for GenAI](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/)
 13. [GenAI app developer workflow](https://learn.microsoft.com/en-us/azure/databricks/generative-ai/tutorials/ai-cookbook/genai-developer-workflow)
 14. [Plan and prepare a GenAIOps solution (Microsoft Learn Training)](https://learn.microsoft.com/en-us/training/modules/plan-prepare-genaiops/)
--- a/skills/ms-ai-engineering/references/mlops-genaiops/governance-audit-ml-operations.md
+++ b/skills/ms-ai-engineering/references/mlops-genaiops/governance-audit-ml-operations.md
@ -104,7 +104,7 @@ Azure Policy lar deg definere *guardrails* for hvilke modeller som kan deployes,
 **Kilder:**

 - [Audit and manage Azure Machine Learning with Azure Policy](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-integrate-azure-policy?view=azureml-api-2)
- [Azure AI Foundry built-in policies](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/azure-policy)
+- [Azure AI Foundry built-in policies](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/azure-policy)
 - [Govern Azure platform services (PaaS) for AI](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/platform/governance)

 ---
--- a/skills/ms-ai-engineering/references/mlops-genaiops/inferencing-optimization-caching.md
+++ b/skills/ms-ai-engineering/references/mlops-genaiops/inferencing-optimization-caching.md
@ -953,7 +953,7 @@ Diagnostikk:
   *Verifisert: 2026-02-04* — Komplett guide til ONNX Runtime, model conversion, deployment

 2. **Prompt Caching (Azure OpenAI)**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/prompt-caching?view=foundry-classic
+   https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/prompt-caching?view=foundry-classic
   *Verifisert: 2026-02-04* — Official docs for prompt caching, supported models, pricing

 3. **Application Design for AI Workloads on Azure**
--- a/skills/ms-ai-engineering/references/mlops-genaiops/llm-evaluation-production.md
+++ b/skills/ms-ai-engineering/references/mlops-genaiops/llm-evaluation-production.md
@ -1053,16 +1053,16 @@ Production evaluation er ikke komplett uten human review loop. Anbefal:
 ### Primærkilder (Official Microsoft Documentation)

 1. **Azure AI Foundry Evaluation SDK:**
-   [Evaluate your generative AI application locally with the Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/evaluate-sdk) – Comprehensive guide til local og cloud evaluation
+   [Evaluate your generative AI application locally with the Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/evaluate-sdk) – Comprehensive guide til local og cloud evaluation

 2. **Continuous Evaluation for Agents:**
-   [Continuously evaluate your AI agents (preview)](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/continuous-evaluation-agents) – Production monitoring architecture og SDK examples
+   [Continuously evaluate your AI agents (preview)](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/continuous-evaluation-agents) – Production monitoring architecture og SDK examples

 3. **MLflow 3 Evaluation & Monitoring:**
   [Evaluate and monitor AI agents - Azure Databricks](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/) – MLflow 3 evaluation harness og production scorers

 4. **Observability Overview:**
-   [Observability in generative AI - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability) – High-level GenAIOps lifecycle og evaluator taxonomy
+   [Observability in generative AI - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability) – High-level GenAIOps lifecycle og evaluator taxonomy

 5. **Model Monitoring for Generative AI:**
   [Model monitoring for generative AI applications (preview)](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-monitor-generative-ai-applications) – Azure ML Prompt Flow monitoring approach
@ -1071,7 +1071,7 @@ Production evaluation er ikke komplett uten human review loop. Anbefal:
   [Azure AI Evaluation client library for Python](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-evaluation-readme) – API docs for all built-in evaluators

 7. **Agent Monitoring Dashboard:**
-   [Monitor agents with the Agent Monitoring Dashboard (preview)](https://learn.microsoft.com/en-us/azure/ai-foundry/observability/how-to/how-to-monitor-agents-dashboard) – Setup guide for continuous evaluation in Foundry portal
+   [Monitor agents with the Agent Monitoring Dashboard (preview)](https://learn.microsoft.com/en-us/azure/foundry/observability/how-to/how-to-monitor-agents-dashboard) – Setup guide for continuous evaluation in Foundry portal

 ### Sekundærkilder (Community & Research)

--- a/skills/ms-ai-engineering/references/mlops-genaiops/model-evaluation-frameworks.md
+++ b/skills/ms-ai-engineering/references/mlops-genaiops/model-evaluation-frameworks.md
@ -473,15 +473,15 @@ Hvis du kjører massive evalueringer (100K+ samples), vurder PTU for judge model
 ## Kilder og verifisering

 ### Microsoft Learn (Verified via MCP)
-1. [Evaluate generative AI models and applications by using Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — **Verified** — Komplett guide til Foundry UI evaluations, metrics, data mapping.
+1. [Evaluate generative AI models and applications by using Microsoft Foundry](https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — **Verified** — Komplett guide til Foundry UI evaluations, metrics, data mapping.
 2. [Evaluation flows and metrics (Azure ML Prompt Flow)](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-develop-an-evaluation-flow?view=azureml-api-2) — **Verified** — Custom evaluation flows, aggregation nodes.
 3. [MLflow 3 Evaluation and Monitoring](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/) — **Verified** — LLM judges, scorers, production monitoring.
 4. [Large language model end-to-end evaluation](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-llm-evaluation-phase) — **Verified** — RAG-specific metrics (utilization, completeness, relevance).
 5. [Azure AI Evaluation SDK Overview](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-evaluation-readme?view=azure-python) — **Verified** — Python SDK examples, evaluator initialization.
 6. [Test and evaluate AI workloads on Azure](https://learn.microsoft.com/en-us/azure/well-architected/ai/test) — **Verified** — Quality metrics, testing vs. evaluation, baselining strategy.
-7. [Observability in generative AI](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability) — **Verified** — Three-stage evaluation (base model selection, pre-production, production).
-8. [Azure OpenAI Evaluation API](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/evaluations?view=foundry-classic) — **Verified** — REST API, testing criteria, grading process.
-9. [GitHub Action for Evaluation](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluation-github-action?view=foundry-classic) — **Verified** — CI/CD integration.
+7. [Observability in generative AI](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability) — **Verified** — Three-stage evaluation (base model selection, pre-production, production).
+8. [Azure OpenAI Evaluation API](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/evaluations?view=foundry-classic) — **Verified** — REST API, testing criteria, grading process.
+9. [GitHub Action for Evaluation](https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluation-github-action?view=foundry-classic) — **Verified** — CI/CD integration.
 10. [Scorers and LLM judges (MLflow 3)](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/concepts/scorers) — **Verified** — Judge models, accuracy validation, partner-powered AI disclaimers.

 ### Confidence per seksjon
--- a/skills/ms-ai-engineering/references/mlops-genaiops/model-versioning-registry-management.md
+++ b/skills/ms-ai-engineering/references/mlops-genaiops/model-versioning-registry-management.md
@ -541,7 +541,7 @@ az ml model list --registry-name my-registry --query "[?created<'$cutoff_date'].
   - Coverage: CI/CD integration, Azure Pipelines, MLOps automation

 6. **Explore Microsoft Foundry Models**
-   - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/foundry-models-overview?view=foundry-classic
+   - URL: https://learn.microsoft.com/en-us/azure/foundry-classic/concepts/foundry-models-overview?view=foundry-classic
   - Confidence: **Verified** (MCP search results, Feb 2026)
   - Coverage: Model catalog, deployment options, Azure AI Foundry integration

--- a/skills/ms-ai-engineering/references/mlops-genaiops/prompt-flow-production-deployment.md
+++ b/skills/ms-ai-engineering/references/mlops-genaiops/prompt-flow-production-deployment.md
@ -647,9 +647,9 @@ Er dette første gang kunden deployer LLM-basert app?
 ## Kilder og verifisering

 **Microsoft Learn Dokumentasjon:**
-1. [Deploy a flow for real-time inference (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/flow-deploy?view=foundry-classic) – Offisiell guide for deployment via portal
+1. [Deploy a flow for real-time inference (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/flow-deploy?view=foundry-classic) – Offisiell guide for deployment via portal
 2. [GenAIOps with Prompt Flow and GitHub](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-end-to-end-llmops-with-prompt-flow?view=azureml-api-2) – CI/CD pipeline patterns og lifecycle management
-3. [Enable tracing and collect feedback for a flow deployment](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/trace-production-sdk?view=foundry-classic) – Application Insights integration og metrics
+3. [Enable tracing and collect feedback for a flow deployment](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/trace-production-sdk?view=foundry-classic) – Application Insights integration og metrics
 4. [Deploy a flow to online endpoint with CLI/SDK](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-deploy-to-code?view=azureml-api-2) – Advanced deployment configuration (concurrency, FastAPI, etc.)
 5. [Integrate Prompt Flow with DevOps](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-integrate-with-llm-app-devops?view=azureml-api-2) – Local-to-cloud development workflow

--- a/skills/ms-ai-engineering/references/rag-architecture/citation-tracking.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/citation-tracking.md
@ -284,9 +284,9 @@ result = groundedness_eval(
 ### Verified (MCP-research)
 - [RAG overview in Azure AI Search](https://learn.microsoft.com/en-us/azure/search/retrieval-augmented-generation-overview)
 - [Agentic retrieval overview](https://learn.microsoft.com/en-us/azure/search/agentic-retrieval-overview)
- [Transparency note for Azure AI Search](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/search/transparency-note)
+- [Transparency note for Azure AI Search](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/search/transparency-note)
 - [Grounding data design](https://learn.microsoft.com/en-us/azure/well-architected/ai/grounding-data-design)
- [Azure AI Foundry agents - AI Search tools](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/ai-search)
+- [Azure AI Foundry agents - AI Search tools](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/ai-search)

 ### Baseline (modellkunnskap)
 - Norsk lovgivning (Forvaltningsloven, Offentleglova, Arkivloven)
--- a/skills/ms-ai-engineering/references/rag-architecture/graphrag-knowledge-graphs.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/graphrag-knowledge-graphs.md
@ -280,7 +280,7 @@ GraphRAG introduserer spesifikke personvernrisiki i offentlig sektor:
 | CosmosAIGraph arkitektur | https://learn.microsoft.com/en-us/azure/cosmos-db/gen-ai/cosmos-ai-graph | ✅ Verified (2026-02) |
 | Graph semantics i KQL | https://learn.microsoft.com/en-us/kusto/query/graph-semantics-overview | ✅ Verified (2026-02) |
 | Entity Recognition skill (v3) | https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-entity-recognition-v3 | ✅ Verified (2026-02) |
-| Azure AI Search transparency note | https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/search/transparency-note | ✅ Verified (2026-02) |
+| Azure AI Search transparency note | https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/search/transparency-note | ✅ Verified (2026-02) |
 | RAG solution design guide | https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-solution-design-and-evaluation-guide | ✅ Verified (2026-02) |
 | Labeled Property Graphs (LPG) | https://learn.microsoft.com/en-us/fabric/graph/graph-data-models | ✅ Verified (2026-02) |

--- a/skills/ms-ai-engineering/references/rag-architecture/late-chunking-patterns.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/late-chunking-patterns.md
@ -244,5 +244,5 @@ for i, chunk in enumerate(chunks):
 | arXiv:2409.04701 (forskningspaper) | **Verified** | [arxiv.org](https://arxiv.org/abs/2409.04701) |
 | Jina Embeddings on Azure Marketplace | **Verified** | [azuremarketplace.microsoft.com](https://azuremarketplace.microsoft.com/en-us/marketplace/apps/jinaai.jina-embeddings-v4) |
 | Jina Embeddings v3 announcement | **Verified** | [jina.ai](https://jina.ai/news/jina-embeddings-v3-a-frontier-multilingual-embedding-model/) |
-| Azure OpenAI Embeddings | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/tutorials/embeddings) |
+| Azure OpenAI Embeddings | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/azure/foundry/openai/tutorials/embeddings) |
 | Late Chunking tutorial (DataCamp) | **Baseline** | [datacamp.com](https://www.datacamp.com/tutorial/late-chunking) |
--- a/skills/ms-ai-engineering/references/rag-architecture/rag-context-windows.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/rag-context-windows.md
@ -388,7 +388,7 @@ Hvis du har 10,000 queries per måned: **11,300 NOK/måned** (kun LLM-kostnad, i
 ### Microsoft Learn (Verified via MCP)

 1. **Azure OpenAI Assistants API — Context Window Management**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/assistants#context-window-management
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/assistants#context-window-management
   *Dekning: max_prompt_tokens, max_completion_tokens, truncation strategy, File Search recommendations*
   **Confidence: Verified**

@ -398,12 +398,12 @@ Hvis du har 10,000 queries per måned: **11,300 NOK/måned** (kun LLM-kostnad, i
   **Confidence: Verified**

 3. **Azure OpenAI in Microsoft Foundry Models — Quotas and Limits**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quotas-limits
+   https://learn.microsoft.com/en-us/azure/foundry/openai/quotas-limits
   *Dekning: TPM limits per model, context window sizes, rate limits*
   **Confidence: Verified**

 4. **Azure OpenAI On Your Data — Token Usage Estimation**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data
   *Dekning: Intent prompt vs. generation prompt token breakdown, RAG pipeline token costs*
   **Confidence: Verified**

@ -413,12 +413,12 @@ Hvis du har 10,000 queries per måned: **11,300 NOK/måned** (kun LLM-kostnad, i
   **Confidence: Verified**

 6. **Chat Markup Language ChatML — Managing Conversations**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chat-markup-language#preventing-unsafe-user-inputs
+   https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/responses#preventing-unsafe-user-inputs
   *Dekning: Token counting med tiktoken, conversation history truncation*
   **Confidence: Verified**

 7. **Code Sample: Token Counting with tiktoken (Python)**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chatgpt
+   https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/chatgpt
   *Dekning: Praktisk implementasjon av token management i conversation loops*
   **Confidence: Verified**

--- a/skills/ms-ai-engineering/references/rag-architecture/rag-cost-optimization.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/rag-cost-optimization.md
@ -501,15 +501,15 @@ Metrics:
 - [Vector compression best practices](https://techcommunity.microsoft.com/blog/azure-ai-services-blog/azure-ai-search-cut-vector-costs-up-to-92-5-with-new-compression-techniques/4404866) — *Verified: Compression techniques (92.5% reduction)*

 **Azure OpenAI Cost Management:**
- [Plan and manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs) — *Verified: Token-based billing, fine-tuning costs*
- [Azure OpenAI Batch API](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch) — *Verified: 50% cost reduction for batch workloads*
- [Fine-tuning cost management](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/fine-tuning-cost-management) — *Verified: Hosting + inference + training costs*
+- [Plan and manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs) — *Verified: Token-based billing, fine-tuning costs*
+- [Azure OpenAI Batch API](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch) — *Verified: 50% cost reduction for batch workloads*
+- [Fine-tuning cost management](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/fine-tuning-cost-management) — *Verified: Hosting + inference + training costs*

 **RAG Architecture & Optimization:**
 - [RAG design and evaluation guide](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-solution-design-and-evaluation-guide) — *Verified: End-to-end RAG considerations*
 - [RAG chunking economics](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-chunking-phase#understand-chunking-economics) — *Verified: Chunking cost optimization*
 - [RAG embedding economics](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-generate-embeddings#understand-embedding-economics) — *Verified: Embedding model selection trade-offs*
- [Retrieval cost and latency considerations](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/retrieval-augmented-generation#cost-and-latency-considerations) — *Verified: Query cost analysis*
+- [Retrieval cost and latency considerations](https://learn.microsoft.com/en-us/azure/foundry/concepts/retrieval-augmented-generation#cost-and-latency-considerations) — *Verified: Query cost analysis*

 **Cloud Adoption Framework:**
 - [Manage AI costs](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/manage#manage-ai-costs) — *Verified: Enterprise cost governance*
--- a/skills/ms-ai-engineering/references/rag-architecture/rag-evaluation-frameworks.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/rag-evaluation-frameworks.md
@ -311,11 +311,11 @@ Bruk `mlflow.log_feedback()` med `AssessmentSourceType.HUMAN` for å logge menne
 ## Kilder og verifisering

 ### Verified (MCP-research)
- [Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/evaluate-sdk)
+- [Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/evaluate-sdk)
 - [RAG LLM Evaluation Phase](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-llm-evaluation-phase)
 - [RAG Solution Design Guide](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-solution-design-and-evaluation-guide)
- [Built-in RAG Evaluators](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/evaluation-evaluators/rag-evaluators)
- [Azure AI Foundry Observability](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability)
+- [Built-in RAG Evaluators](https://learn.microsoft.com/en-us/azure/foundry/concepts/evaluation-evaluators/rag-evaluators)
+- [Azure AI Foundry Observability](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability)
 - [RAG Experiment Accelerator](https://github.com/microsoft/rag-experiment-accelerator)

 ### Baseline (modellkunnskap)
--- a/skills/ms-ai-engineering/references/rag-architecture/rag-hallucination-mitigation.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/rag-hallucination-mitigation.md
@ -385,9 +385,9 @@ Hvis AI-systemet gir feil informasjon som fører til skade:
 **Microsoft Learn (Verified via MCP):**
 - [Groundedness Detection Concepts](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/groundedness) — **Verified**
 - [Groundedness Detection Quickstart](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/quickstart-groundedness) — **Verified**
- [Groundedness Detection Filter](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-groundedness) — **Verified**
- [Prompt Engineering Techniques](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering) — **Verified**
- [Transparency Note: Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note) — **Verified**
+- [Groundedness Detection Filter](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-groundedness) — **Verified**
+- [Prompt Engineering Techniques](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering) — **Verified**
+- [Transparency Note: Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note) — **Verified**
 - [RAG Solution Design Guide](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-solution-design-and-evaluation-guide) — **Verified**
 - [Secure Multitenant RAG](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/secure-multitenant-rag) — **Verified**

--- a/skills/ms-ai-engineering/references/rag-architecture/rag-iterative-refinement.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/rag-iterative-refinement.md
@ -418,7 +418,7 @@ public async Task ApplyRetentionPolicyAsync()
 | [Multi-turn conversations with an agent](https://learn.microsoft.com/en-us/agent-framework/tutorials/agents/multi-turn-conversation) | Agent Framework session management | **Verified** |
 | [Chat history (Semantic Kernel)](https://learn.microsoft.com/en-us/semantic-kernel/concepts/ai-services/chat-completion/chat-history) | ChatHistory API, reduction strategies | **Verified** |
 | [Using memory with Agents](https://learn.microsoft.com/en-us/semantic-kernel/frameworks/agent/agent-memory) | Whiteboard memory, memory providers | **Verified** |
-| [Use the Azure OpenAI web app](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/use-web-app) | Cosmos DB chat history enablement | **Verified** |
+| [Use the Azure OpenAI web app](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/use-web-app) | Cosmos DB chat history enablement | **Verified** |
 | [RAG with Azure DocumentDB](https://learn.microsoft.com/en-us/azure/documentdb/rag) | History-aware retrieval chains | **Verified** |
 | [Storing Chat History in 3rd Party Storage](https://learn.microsoft.com/en-us/agent-framework/tutorials/agents/third-party-chat-history-storage) | Custom ChatHistoryProvider | **Verified** |
 | [IChatClient documentation](https://learn.microsoft.com/en-us/dotnet/ai/ichatclient) | Stateless vs stateful clients | **Verified** |
--- a/skills/ms-ai-engineering/references/rag-architecture/rag-security-rbac.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/rag-security-rbac.md
@ -473,7 +473,7 @@ Authorization: Bearer <user-token>
   - Dekning: Hierarchical permissions, POSIX-like ACLs, indexer configuration

 5. **Azure OpenAI On Your Data - Document-level access control**
-   - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/on-your-data-configuration#document-level-access-control
+   - URL: https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/on-your-data-configuration#document-level-access-control
   - Confidence: **Verified** (MCP-search 2026-02)
   - Dekning: RAG integration, filter parameter, group_ids field mapping

@ -493,7 +493,7 @@ Authorization: Bearer <user-token>
   - Dekning: RAG challenges, security & governance

 9. **Retrieval augmented generation (RAG) and indexes (AI Foundry)**
-   - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/retrieval-augmented-generation?view=foundry-classic
+   - URL: https://learn.microsoft.com/en-us/azure/foundry/concepts/retrieval-augmented-generation?view=foundry-classic
   - Confidence: **Verified** (MCP-search 2026-02)
   - Dekning: Security considerations, access control at retrieval time

--- a/skills/ms-ai-engineering/references/rag-architecture/self-reflective-rag.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/self-reflective-rag.md
@ -265,7 +265,7 @@ Hvis self-reflective RAG reduserer feilaktige svar fra 15% til 5%:

 | Kilde | Konfidens | URL |
 |-------|-----------|-----|
-| RAG Evaluators (Azure AI Foundry) | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/evaluation-evaluators/rag-evaluators) |
+| RAG Evaluators (Azure AI Foundry) | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/azure/foundry/concepts/evaluation-evaluators/rag-evaluators) |
 | RAG LLM Evaluation Phase | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-llm-evaluation-phase) |
 | Semantic Kernel Agent RAG | **Verified** | [learn.microsoft.com](https://learn.microsoft.com/en-us/semantic-kernel/frameworks/agent/agent-rag) |
 | Corrective RAG (CRAG) paper | **Verified** | [arxiv.org](https://arxiv.org/abs/2401.15884) |
--- a/skills/ms-ai-engineering/references/rag-architecture/streaming-rag-responses.md
+++ b/skills/ms-ai-engineering/references/rag-architecture/streaming-rag-responses.md
@ -407,11 +407,11 @@ Ved bruk av streaming med `code_interpreter` tool:

 ### Verified (fra MCP microsoft-learn)

- Azure OpenAI Responses API streaming: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/responses (Verified: 2026-02)
+- Azure OpenAI Responses API streaming: https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/responses (Verified: 2026-02)
 - Semantic Kernel Agent streaming: https://learn.microsoft.com/en-us/semantic-kernel/frameworks/agent/agent-streaming (Verified: 2026-02)
 - SSE med Application Gateway: https://learn.microsoft.com/en-us/azure/application-gateway/use-server-sent-events (Verified: 2026-02)
- Azure OpenAI REST API reference: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/reference (Verified: 2026-02)
- Chat Completions API streaming: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/reference#chat-completions (Verified: 2026-02)
+- Azure OpenAI REST API reference: https://learn.microsoft.com/en-us/azure/foundry/openai/reference (Verified: 2026-02)
+- Chat Completions API streaming: https://learn.microsoft.com/en-us/azure/foundry/openai/reference#chat-completions (Verified: 2026-02)

 ### Baseline (modellkunnskap)