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

skills/ms-ai-advisor/references/architecture/cost-models.md

@@ -587,7 +587,7 @@ Azure AI Foundry er en **orkestreringsplattform** som benytter flere Azure-tjene
 - [Azure Cost Management](https://azure.microsoft.com/services/cost-management/)
 
 **Dokumentasjon:**
-- [Azure OpenAI Cost Management](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/manage-costs)
+- [Azure OpenAI Cost Management](https://learn.microsoft.com/azure/foundry/concepts/manage-costs)
 - [Copilot Studio Billing and management](https://learn.microsoft.com/microsoft-copilot-studio/billing-rates-and-management) — Verified (MCP 2026-04)
 - [AI Builder Credit Management](https://learn.microsoft.com/ai-builder/credit-management)
 

skills/ms-ai-advisor/references/architecture/migration-patterns.md

@@ -1182,7 +1182,7 @@ Base effort: 200 timer
 ### Microsoft Learn
 - [Azure Migration Guide](https://learn.microsoft.com/azure/cloud-adoption-framework/migrate/)
 - [Copilot Studio Migration](https://learn.microsoft.com/microsoft-copilot-studio/unified-authoring-conversion)
-- [Azure AI Foundry Documentation](https://learn.microsoft.com/azure/ai-foundry/)
+- [Azure AI Foundry Documentation](https://learn.microsoft.com/azure/foundry/)
 
 ### Verktøy
 - **Azure Migrate:** Assessment og migrering av workloads

skills/ms-ai-advisor/references/architecture/poc-template.md

@@ -925,7 +925,7 @@ Legg til ekstra tid hvis:
 ### Microsoft Documentation
 - [AI Adoption Framework (CAF)](https://learn.microsoft.com/azure/cloud-adoption-framework/scenarios/ai/)
 - [Copilot Studio Implementation Guidance](https://learn.microsoft.com/microsoft-copilot-studio/guidance/overview)
-- [Azure AI Foundry Evaluation](https://learn.microsoft.com/azure/ai-foundry/concepts/evaluation-evaluators/)
+- [Azure AI Foundry Evaluation](https://learn.microsoft.com/azure/foundry/how-to/evaluate-generative-ai-app)
 - [Responsible AI Standard](https://www.microsoft.com/ai/responsible-ai)
 
 ### Tools

skills/ms-ai-advisor/references/architecture/regional-availability-verification.md

@@ -248,9 +248,9 @@ Når en tjeneste ikke er tilgjengelig i Norway East:
 | Ressurs | URL | Oppdateringsfrekvens |
 |---------|-----|---------------------|
 | Azure Products by Region | https://azure.microsoft.com/en-us/explore/global-infrastructure/products-by-region | Fortløpende |
-| Azure OpenAI Models & Region | https://learn.microsoft.com/azure/ai-foundry/openai/concepts/models | Ved modellendringer |
+| Azure OpenAI Models & Region | https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure | Ved modellendringer |
 | Azure AI Search Regions | https://learn.microsoft.com/azure/search/search-region-support | Ved regionsendringer |
-| Microsoft Foundry Regions | https://learn.microsoft.com/azure/ai-foundry/reference/region-support | Ved regionsendringer |
+| Microsoft Foundry Regions | https://learn.microsoft.com/azure/foundry/reference/region-support | Ved regionsendringer |
 | Azure Status | https://status.azure.com | Sanntid |
 | Azure Updates | https://azure.microsoft.com/updates | Daglig |
 

skills/ms-ai-advisor/references/copilot-extensibility/copilot-api-rate-limiting-resilience.md

@@ -244,7 +244,7 @@ while True:
 
 **Use case:** Store batch-operasjoner (Azure OpenAI, Azure AI Foundry).
 
-**Verified:** [Batch deployments - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch)
+**Verified:** [Batch deployments - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch)
 
 ---
 
@@ -299,7 +299,7 @@ while True:
 - Implementer retry logic med exponential backoff
 - Unngå skarpe workload-endringer (gradvis økning)
 
-**Verified:** [Quotas and limits - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quotas-limits), [Manage quota - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/quota)
+**Verified:** [Quotas and limits - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/quotas-limits), [Manage quota - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/quota)
 
 ### Copilot Studio
 
@@ -484,9 +484,9 @@ while True:
 3. [Circuit Breaker pattern - Cloud-Native .NET](https://learn.microsoft.com/en-us/dotnet/architecture/cloud-native/application-resiliency-patterns)
 4. [What is rate limiting? - Microsoft Cloud Dev](https://learn.microsoft.com/en-us/microsoft-cloud/dev/dev-proxy/concepts/what-is-rate-limiting)
 5. [How to handle API throttling - Microsoft Cloud Dev](https://learn.microsoft.com/en-us/microsoft-cloud/dev/dev-proxy/concepts/how-to-handle-api-throttling)
-6. [Azure OpenAI quotas and limits](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/quotas-limits)
-7. [Manage Azure OpenAI quota](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/quota)
-8. [Batch deployments - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch)
+6. [Azure OpenAI quotas and limits](https://learn.microsoft.com/en-us/azure/foundry/openai/quotas-limits)
+7. [Manage Azure OpenAI quota](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/quota)
+8. [Batch deployments - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch)
 9. [Resolve throttling errors in Copilot Studio agents](https://learn.microsoft.com/en-us/troubleshoot/power-platform/copilot-studio/licensing/throttling-errors-agents)
 10. [Error codes - Copilot Studio](https://learn.microsoft.com/en-us/troubleshoot/power-platform/copilot-studio/authoring/error-codes)
 11. [Optimize bot with rate limiting in Teams](https://learn.microsoft.com/en-us/microsoftteams/platform/bots/how-to/rate-limit)

skills/ms-ai-advisor/references/copilot-extensibility/copilot-context-window-optimization.md

@@ -538,11 +538,11 @@ Response + Citations
 **MCP-verified sources (microsoft-learn):**
 
 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
    - Verified: max_prompt_tokens, max_completion_tokens, truncation_strategy
 
 2. **Troubleshooting and best practices for Azure OpenAI On Your Data**
-   - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/on-your-data-best-practices
+   - https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/on-your-data-best-practices
    - Verified: topNDocuments, strictness, chunk_size, workflow funnel
 
 3. **Quotas and limits for Copilot Studio**
@@ -558,7 +558,7 @@ Response + Citations
    - Verified: Known limitations, no long-running task support, context limits
 
 6. **Azure OpenAI Predicted Outputs**
-   - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/predicted-outputs
+   - https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/predicted-outputs
    - Verified: Prediction parameter for latency optimization
 
 7. **Copilot handoff (Teams Bot Framework)**

skills/ms-ai-advisor/references/development/agent-framework.md

@@ -465,7 +465,7 @@ result = await agent.run()  # Automatisk planning
 ## Ressurser
 
 - [Agent Framework Documentation](https://learn.microsoft.com/azure/ai-services/agents)
-- [Azure AI Foundry Agent Service](https://learn.microsoft.com/azure/ai-foundry/agent-service)
+- [Azure AI Foundry Agent Service](https://learn.microsoft.com/azure/foundry/agents/overview)
 - [Migration Guide from Semantic Kernel](https://learn.microsoft.com/azure/ai-services/agents/migrate-semantic-kernel)
 - [GitHub Samples](https://github.com/azure-samples/ai-agent-framework)
 

skills/ms-ai-advisor/references/platforms/azure-ai-foundry.md

@@ -371,18 +371,18 @@ Microsoft.CognitiveServices/account (kind: AIServices)
 
 Adapted from Microsoft Learn documentation ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)):
 
-- [What is Microsoft Foundry?](https://learn.microsoft.com/azure/ai-foundry/what-is-foundry?view=foundry-classic)
-- [What's new in Microsoft Foundry (December 2025)](https://learn.microsoft.com/azure/ai-foundry/whats-new-foundry?view=foundry-classic)
-- [What's new in Azure OpenAI](https://learn.microsoft.com/azure/ai-foundry/openai/whats-new?view=foundry-classic)
-- [What's new in Foundry Agent Service](https://learn.microsoft.com/azure/ai-foundry/agents/whats-new?view=foundry-classic)
-- [GPT-5 models](https://learn.microsoft.com/azure/ai-foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic)
-- [Build a workflow in Microsoft Foundry](https://learn.microsoft.com/azure/ai-foundry/agents/concepts/workflow?view=foundry)
-- [Foundry Local](https://learn.microsoft.com/azure/ai-foundry/foundry-local/what-is-foundry-local?view=foundry-classic)
-- [Computer Use (preview)](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/computer-use?view=foundry-classic)
-- [Deep Research tool](https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools-classic/deep-research?view=foundry-classic)
-- [A2A Agent endpoint (preview)](https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools/agent-to-agent?view=foundry)
-- [MCP tool](https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools-classic/model-context-protocol?view=foundry-classic)
-- [Model region availability](https://learn.microsoft.com/azure/ai-foundry/openai/concepts/models)
+- [What is Microsoft Foundry?](https://learn.microsoft.com/azure/foundry/what-is-foundry?view=foundry-classic)
+- [What's new in Microsoft Foundry (December 2025)](https://learn.microsoft.com/azure/foundry/whats-new-foundry?view=foundry-classic)
+- [What's new in Azure OpenAI](https://learn.microsoft.com/azure/foundry-classic/openai/whats-new?view=foundry-classic)
+- [What's new in Foundry Agent Service](https://learn.microsoft.com/azure/foundry-classic/agents/whats-new?view=foundry-classic)
+- [GPT-5 models](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic)
+- [Build a workflow in Microsoft Foundry](https://learn.microsoft.com/azure/foundry/agents/concepts/workflow?view=foundry)
+- [Foundry Local](https://learn.microsoft.com/azure/foundry-local/what-is-foundry-local?view=foundry-classic)
+- [Computer Use (preview)](https://learn.microsoft.com/azure/foundry-classic/openai/how-to/computer-use?view=foundry-classic)
+- [Deep Research tool](https://learn.microsoft.com/azure/foundry-classic/agents/how-to/tools-classic/deep-research?view=foundry-classic)
+- [A2A Agent endpoint (preview)](https://learn.microsoft.com/azure/foundry/agents/how-to/tools/agent-to-agent?view=foundry)
+- [MCP tool](https://learn.microsoft.com/azure/foundry-classic/agents/how-to/tools-classic/model-context-protocol?view=foundry-classic)
+- [Model region availability](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure)
 
 Content has been translated to Norwegian, reorganized, and augmented with decision guidance.
 

skills/ms-ai-advisor/references/platforms/model-catalog-2026.md

@@ -390,15 +390,15 @@ Trenger kunden open-source/selvhostet-alternativ?
 
 Adapted from Microsoft Learn documentation ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)):
 
-- [Foundry Models sold directly by Azure (azure-openai)](https://learn.microsoft.com/azure/ai-foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic)
-- [Foundry Models sold directly by Azure (azure-direct-others)](https://learn.microsoft.com/azure/ai-foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic&pivots=azure-direct-others)
-- [Azure OpenAI in Azure AI Foundry Models — model overview](https://learn.microsoft.com/azure/ai-foundry/openai/concepts/models)
-- [GPT-5 vs GPT-4.1: choosing the right model](https://learn.microsoft.com/azure/ai-foundry/foundry-models/how-to/model-choice-guide?view=foundry-classic)
-- [Azure OpenAI reasoning models](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/reasoning?view=foundry-classic)
-- [PTU costs and billing](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding?view=foundry-classic)
-- [Foundry Models from partners and community (Phi)](https://learn.microsoft.com/azure/ai-foundry/foundry-models/concepts/models-from-partners?view=foundry-classic)
-- [Azure OpenAI models and regions for Foundry Agent Service](https://learn.microsoft.com/azure/ai-foundry/agents/concepts/model-region-support?view=foundry-classic)
-- [Azure OpenAI quotas and limits](https://learn.microsoft.com/azure/ai-foundry/openai/quotas-limits?view=foundry-classic)
+- [Foundry Models sold directly by Azure (azure-openai)](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic)
+- [Foundry Models sold directly by Azure (azure-direct-others)](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure?view=foundry-classic&pivots=azure-direct-others)
+- [Azure OpenAI in Azure AI Foundry Models — model overview](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure)
+- [GPT-5 vs GPT-4.1: choosing the right model](https://learn.microsoft.com/azure/foundry/foundry-models/how-to/model-choice-guide?view=foundry-classic)
+- [Azure OpenAI reasoning models](https://learn.microsoft.com/azure/foundry/openai/how-to/reasoning?view=foundry-classic)
+- [PTU costs and billing](https://learn.microsoft.com/azure/foundry/openai/concepts/provisioned-throughput-billing?view=foundry-classic)
+- [Foundry Models from partners and community (Phi)](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-from-partners?view=foundry-classic)
+- [Azure OpenAI models and regions for Foundry Agent Service](https://learn.microsoft.com/azure/foundry-classic/agents/concepts/model-region-support?view=foundry-classic)
+- [Azure OpenAI quotas and limits](https://learn.microsoft.com/azure/foundry/openai/quotas-limits?view=foundry-classic)
 
 Content translated to Norwegian, reorganized, and augmented with decision guidance for Norwegian public sector.
 

skills/ms-ai-advisor/references/prompt-engineering/adversarial-prompting-and-jailbreaks.md

@@ -760,11 +760,11 @@ Start: AI system security design
    *Verifisert: januar 2026, omfatter AI-1 til AI-7 controls*
 
 3. **Azure AI Red Teaming Agent:**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/ai-red-teaming-agent
+   https://learn.microsoft.com/en-us/azure/foundry/concepts/ai-red-teaming-agent
    *Verifisert: januar 2026, Public Preview*
 
 4. **Content Filtering (default policies):**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/default-safety-policies
+   https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/default-safety-policies
    *Verifisert: januar 2026, GA*
 
 5. **Microsoft Defender for AI Services:**

skills/ms-ai-advisor/references/prompt-engineering/chain-of-thought-prompting.md

@@ -474,11 +474,11 @@ Chain-of-thought øker token-forbruk betydelig:
 
 | Kilde | Konfidensnivå | Verifisert dato |
 |-------|---------------|-----------------|
-| [Prompt engineering techniques - Chain of thought prompting](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering#chain-of-thought-prompting) | **Verified** | 2026-02 |
-| [Azure OpenAI On Your Data - Best practices (Chain-of-thought prompting)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data#best-practices) | **Verified** | 2026-02 |
-| [Azure OpenAI Evaluation (Preview) - Factuality (uses CoT internally)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/evaluations#types-of-testing-criteria) | **Verified** | 2026-02 |
-| [Azure OpenAI reasoning models (o1, o3, GPT-5)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/reasoning) | **Verified** | 2026-02 |
-| [Transparency note for Azure OpenAI - Chain-of-thought capabilities](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note?view=foundry-classic#capabilities) | **Verified** | 2026-02 |
+| [Prompt engineering techniques - Chain of thought prompting](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering#chain-of-thought-prompting) | **Verified** | 2026-02 |
+| [Azure OpenAI On Your Data - Best practices (Chain-of-thought prompting)](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data#best-practices) | **Verified** | 2026-02 |
+| [Azure OpenAI Evaluation (Preview) - Factuality (uses CoT internally)](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/evaluations#types-of-testing-criteria) | **Verified** | 2026-02 |
+| [Azure OpenAI reasoning models (o1, o3, GPT-5)](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/reasoning) | **Verified** | 2026-02 |
+| [Transparency note for Azure OpenAI - Chain-of-thought capabilities](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note?view=foundry-classic#capabilities) | **Verified** | 2026-02 |
 
 ### Baseline-kunnskap (fra Claude-modell)
 
@@ -493,7 +493,7 @@ Chain-of-thought øker token-forbruk betydelig:
 
 1. **microsoft_docs_search:** "chain of thought prompting Azure OpenAI" → 10 resultater
 2. **microsoft_code_sample_search:** "chain of thought prompt examples" → 20 code snippets
-3. **microsoft_docs_fetch:** [Azure OpenAI reasoning models](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/reasoning) → Full dokumentasjon hentet
+3. **microsoft_docs_fetch:** [Azure OpenAI reasoning models](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/reasoning) → Full dokumentasjon hentet
 
 **Totalt:** 4 MCP-kall, 3 unike Microsoft Learn-kilder.
 

skills/ms-ai-advisor/references/prompt-engineering/domain-specific-prompt-optimization.md

@@ -558,19 +558,19 @@ Basert på testing (Azure OpenAI dokumentasjon):
 ### Microsoft Learn dokumentasjon (fetched via MCP 2026-02-04)
 
 1. **Prompt engineering techniques** (Azure OpenAI)
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering
+   https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering
    *Source for: Best practices, few-shot learning, chain-of-thought, output structure*
 
 2. **Azure OpenAI On Your Data**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data
    *Source for: RAG configuration, field mapping, strictness, multi-lingual support, token estimation*
 
 3. **Transparency note for Azure OpenAI**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note
+   https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note
    *Source for: Model capabilities, limitations, responsible AI considerations*
 
 4. **Azure OpenAI FAQ**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/faq
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/faq
    *Source for: Language handling, model behavior, grounding strategies*
 
 5. **Apply prompt engineering with Azure OpenAI Service - Training**

skills/ms-ai-advisor/references/prompt-engineering/error-handling-and-fallback-prompting.md

@@ -686,14 +686,14 @@ User Request
 ## Kilder og verifisering
 
 **Primærkilder (Microsoft Learn):**
-1. [Azure OpenAI supported programming languages - Error handling](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/supported-languages) – Offisiell dokumentasjon for retry-mekanismer i alle SDK-er
+1. [Azure OpenAI supported programming languages - Error handling](https://learn.microsoft.com/en-us/azure/foundry/openai/supported-languages) – Offisiell dokumentasjon for retry-mekanismer i alle SDK-er
 2. [Architecture strategies for self-preservation](https://learn.microsoft.com/en-us/azure/well-architected/reliability/self-preservation) – Azure Well-Architected Framework reliability-mønstre
 3. [Azure OpenAI Priority-Based Load Balancer (GitHub)](https://github.com/Azure-Samples/openai-aca-lb) – Referanseimplementasjon av smart load balancing
-4. [Troubleshooting Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/on-your-data-best-practices) – Best practices for debugging og error handling
+4. [Troubleshooting Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/on-your-data-best-practices) – Best practices for debugging og error handling
 5. [llm-content-safety policy (APIM)](https://learn.microsoft.com/en-us/azure/api-management/llm-content-safety-policy) (Re-verified MCP 2026-04) – Content safety enforcement i API Management. Policy-attributter: backend-id, shield-prompt, enforce-on-completions, window-size, output-type, threshold (0-7), blocklists.
 
 **Sekundærkilder:**
-6. [Azure OpenAI FAQ](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/faq) – Vanlige feilsituasjoner og workarounds
+6. [Azure OpenAI FAQ](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/faq) – Vanlige feilsituasjoner og workarounds
 7. [OWASP Top 10 for LLM - Improper Output Handling](https://genai.owasp.org/llmrisk/llm052025-improper-output-handling/) – Sikkerhetshensyn ved output validation
 8. [Reliability Maturity Model](https://learn.microsoft.com/en-us/azure/well-architected/reliability/maturity-model) – Graceful degradation og testing
 

skills/ms-ai-advisor/references/prompt-engineering/few-shot-learning-techniques.md

@@ -510,11 +510,11 @@ User Query
 **Verified (MCP microsoft-learn, januar 2026):**
 
 1. **Prompt engineering techniques** (Azure AI Foundry)
-   - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering
+   - https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering
    - Seksjon: Few-shot learning, Zero-shot learning, Examples
 
 2. **Work with chat completions models**
-   - 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
    - Seksjon: Few-shot learning with chat completion
 
 3. **Zero-shot and few-shot learning** (.NET AI conceptual) (Re-verified MCP 2026-04)
@@ -522,11 +522,11 @@ User Query
    - Primære use cases, performance baselines, caveats (false patterns, token limits, reasoning gaps)
 
 4. **Chat Markup Language ChatML**
-   - https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chat-markup-language
+   - https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/responses
    - Few-shot eksempler i ChatML-format
 
 5. **Transparency note for Azure OpenAI**
-   - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note
+   - https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note
    - In-context learning: Zero-shot, One-shot, Few-shot definitioner
 
 **Code samples verified:**

skills/ms-ai-advisor/references/prompt-engineering/function-calling-and-tool-use.md

@@ -272,7 +272,7 @@ assistant = client.beta.assistants.create(
 
 ### Azure Logic Apps
 
-[Azure Logic Apps kan integreres](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/assistants-logic-apps) med Assistants API for å håndtere function execution.
+[Azure Logic Apps kan integreres](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/assistants-logic-apps) med Assistants API for å håndtere function execution.
 
 ### On Your Data (Azure AI Search + OpenAI)
 
@@ -421,7 +421,7 @@ Function calling påvirker kostnaden på flere måter:
 - Start med én enkel funksjon (f.eks. `get_current_time`)
 - Bruk `tool_choice: "auto"` og observer modellens oppførsel
 - Implementer robust error handling før produksjon
-- Les Microsoft's [responsible AI guidelines](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/overview)
+- Les Microsoft's [responsible AI guidelines](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/overview)
 
 **Viderekomne (har bygget noen agenter):**
 - Implementer parallel function calling for bedre performance
@@ -439,11 +439,11 @@ Function calling påvirker kostnaden på flere måter:
 
 **Verified (fra Microsoft Learn MCP-research):**
 
-1. [How to use function calling with Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/function-calling) — **Konfidensnivå: Høy** (offisiell dokumentasjon, oppdatert januar 2026)
+1. [How to use function calling with Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/function-calling) — **Konfidensnivå: Høy** (offisiell dokumentasjon, oppdatert januar 2026)
 2. [Understand OpenAI function calling](https://learn.microsoft.com/en-us/dotnet/ai/conceptual/understanding-openai-functions) — **Konfidensnivå: Høy** (konseptuell guide med Semantic Kernel-eksempler)
-3. [Azure OpenAI Assistants function calling](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/assistant-functions) — **Konfidensnivå: Høy** (Assistants API-spesifikk dokumentasjon)
-4. [Fine-tuning functions](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/fine-tuning-functions) — **Konfidensnivå: Høy** (for advanced use cases)
-5. [Structured outputs](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/structured-outputs) — **Konfidensnivå: Høy** (komplementær teknikk til function calling)
+3. [Azure OpenAI Assistants function calling](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/assistant-functions) — **Konfidensnivå: Høy** (Assistants API-spesifikk dokumentasjon)
+4. [Fine-tuning functions](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/fine-tuning-functions) — **Konfidensnivå: Høy** (for advanced use cases)
+5. [Structured outputs](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/structured-outputs) — **Konfidensnivå: Høy** (komplementær teknikk til function calling)
 
 **Baseline (fra modellkunnskap januar 2025):**
 

skills/ms-ai-advisor/references/prompt-engineering/grounding-and-knowledge-injection.md

@@ -496,12 +496,12 @@ Sources:
 ## Kilder og verifisering
 
 **MCP-kilder (Verified):**
-1. Microsoft Learn: [Prompt Engineering Techniques](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering) – Groundedness context, citation best practices
-2. Microsoft Learn: [Groundedness Detection Filter](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-groundedness) – RAG definition, ungroundedness detection
+1. Microsoft Learn: [Prompt Engineering Techniques](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering) – Groundedness context, citation best practices
+2. Microsoft Learn: [Groundedness Detection Filter](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-groundedness) – RAG definition, ungroundedness detection
 3. Microsoft Learn: [Secure Multitenant RAG](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/secure-multitenant-rag) – Tenant isolation, API-layer, security trimming
 4. Microsoft Learn: [Copilot Studio Knowledge Sources](https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-copilot-connectors) – SharePoint, connectors, tenant graph grounding
 5. Microsoft Learn: [Web Search in Copilot Studio](https://learn.microsoft.com/en-us/microsoft-copilot-studio/data-privacy-security-web-search) – Bing integration, privacy considerations
-6. Microsoft Learn: [Azure AI Agents (Bing Grounding)](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/web-overview) – Web grounding workflow
+6. Microsoft Learn: [Azure AI Agents (Bing Grounding)](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/web-overview) – Web grounding workflow
 
 **Konfidensnivå per seksjon:**
 | Seksjon | Konfidensnivå | Kilde |

skills/ms-ai-advisor/references/prompt-engineering/multi-turn-conversation-management.md

@@ -294,7 +294,7 @@ AgentSession resumedSession = await agent.DeserializeSessionAsync(serializedSess
 | gpt-35-turbo | 16K tokens | 14K |
 | o1, o3-mini, o4-mini | 128K-200K | Varierer per modell |
 
-**Viktig:** Sjekk alltid [models page](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models) for oppdaterte limits.
+**Viktig:** Sjekk alltid [models page](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure) for oppdaterte limits.
 
 ### Truncation-strategi
 
@@ -638,7 +638,7 @@ User → Copilot Studio → Azure OpenAI
 ### Microsoft Learn (offisiell dokumentasjon)
 
 1. **Work with chat completions models**
-   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
    *Kjernereferanse for Chat Completion API, conversation loop patterns, token management*
 
 2. **Multi-turn conversations with an agent**
@@ -646,19 +646,19 @@ User → Copilot Studio → Azure OpenAI
    *Agent Framework session management, stateless architecture*
 
 3. **Azure OpenAI stored completions & distillation**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/stored-completions
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/stored-completions
    *Stored completions feature, metadata enrichment*
 
 4. **Azure OpenAI 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
    *Token limits per modell, TPM/RPM relationship, rate limiting*
 
 5. **Manage Azure OpenAI quota**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/quota
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/quota
    *Rate limit mechanics, best practices, token counting for rate limits*
 
 6. **Azure OpenAI Assistants API context window management**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/assistants
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/assistants
    *Truncation strategies, max_prompt_tokens, max_completion_tokens*
 
 7. **CLU multi-turn conversations**

skills/ms-ai-advisor/references/prompt-engineering/multimodal-prompt-design.md

@@ -542,10 +542,10 @@ AzureDiagnostics
 ## Kilder og verifisering
 
 **Microsoft Learn dokumentasjon (verifisert 2026-02):**
-- [Use vision-enabled chat models](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/gpt-with-vision) — Offisiell how-to guide for GPT-4o/GPT-4 Turbo with Vision
+- [Use vision-enabled chat models](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/gpt-with-vision) — Offisiell how-to guide for GPT-4o/GPT-4 Turbo with Vision
 - [Image prompt engineering techniques](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/gpt-4-v-prompt-engineering) — Best practices for multimodal prompting
 - [Multimodal search in Azure AI Search](https://learn.microsoft.com/en-us/azure/search/multimodal-search-overview) (Re-verified MCP 2026-04) — RAG-arkitektur; extraction skill-sammenligning (Document Extraction vs Layout vs Content Understanding); verbalization vs direct embeddings; hybrid query-alternativ
-- [Azure OpenAI models](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models) — Modelloversikt og token-kostnader
+- [Azure OpenAI models](https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure) — Modelloversikt og token-kostnader
 - [Quickstart: Multimodal search in Azure portal](https://learn.microsoft.com/en-us/azure/search/search-get-started-portal-image-search) — Wizard-basert oppsett
 - [Get started with multimodal vision chat apps](https://learn.microsoft.com/en-us/azure/developer/ai/get-started-app-chat-vision) — End-to-end sample app med Base64 encoding
 

skills/ms-ai-advisor/references/prompt-engineering/prompt-testing-and-evaluation.md

@@ -1063,15 +1063,15 @@ def grade(sample: dict, item: dict) -> float:
 ## Kilder og verifisering
 
 **Primary Sources (Microsoft Learn):**
-1. [Evaluate generative AI models and applications - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — GA
+1. [Evaluate generative AI models and applications - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — GA
 2. [Evaluation flows and metrics - Azure Machine Learning Prompt Flow](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-develop-an-evaluation-flow?view=azureml-api-2) — GA
 3. [Azure AI Evaluation SDK - Python API](https://learn.microsoft.com/en-us/python/api/overview/azure/ai-evaluation-readme?view=azure-python) — GA
-4. [Agent evaluation with Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/agent-evaluate-sdk?view=foundry-classic) — GA
+4. [Agent evaluation with Azure AI Evaluation SDK](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/agent-evaluate-sdk?view=foundry-classic) — GA
 
 **Code Samples (Microsoft Learn):**
-1. [Cloud evaluation with Azure AI Projects SDK](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/cloud-evaluation?view=foundry-classic)
-2. [Continuous evaluation setup](https://learn.microsoft.com/en-us/azure/ai-foundry/observability/how-to/how-to-monitor-agents-dashboard?view=foundry)
-3. [Custom evaluator registration](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/cloud-evaluation?view=foundry-classic#specify-custom-evaluators)
+1. [Cloud evaluation with Azure AI Projects SDK](https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/cloud-evaluation?view=foundry-classic)
+2. [Continuous evaluation setup](https://learn.microsoft.com/en-us/azure/foundry/observability/how-to/how-to-monitor-agents-dashboard?view=foundry)
+3. [Custom evaluator registration](https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/cloud-evaluation?view=foundry-classic#specify-custom-evaluators)
 
 **Last Verified:** 2026-02-04
 **Version:** Azure AI Foundry v2 (2024-2026), Prompt Flow v1.13+ (2024-2026)

skills/ms-ai-advisor/references/prompt-engineering/real-time-reasoning-performance.md

@@ -485,15 +485,15 @@ Deployment C: Chatbot (variabel prompt, medium output)
 **Primary sources:**
 
 1. **Performance and latency** (Azure OpenAI)
-   [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/latency](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/latency)
+   [https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/latency](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/latency)
    Hentet: januar 2026. Dekker streaming, max_tokens, content filtering, workload separation, metrics.
 
 2. **GPT Realtime API for speech and audio**
-   [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/realtime-audio](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/realtime-audio)
+   [https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/realtime-audio](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/realtime-audio)
    Hentet: januar 2026. Dekker WebRTC/WebSocket, VAD modes, session configuration, supported models.
 
 3. **GPT-4o Realtime API quickstart**
-   [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/realtime-audio-quickstart](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/realtime-audio-quickstart)
+   [https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/realtime-audio](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/realtime-audio)
    Hentet: januar 2026. Kode-eksempler for Python, JavaScript, deployment steps.
 
 4. **Lower speech synthesis latency using Speech SDK** (Re-verified MCP 2026-04)

skills/ms-ai-advisor/references/prompt-engineering/reasoning-models-o1-o3-optimization.md

@@ -516,19 +516,19 @@ Denne kunnskapsreferansen er basert på offisiell Microsoft Learn-dokumentasjon
 **Primary sources:**
 
 1. **Azure OpenAI reasoning models**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/reasoning
+   https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/reasoning
    *Confidence: Verified (MCP fetch 2026-02)*
 
 2. **Azure OpenAI model availability and pricing**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models
+   https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure
    *Confidence: Verified (MCP fetch 2026-02)*
 
 3. **Reasoning models with Microsoft Foundry Models**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/how-to/use-chat-reasoning
+   https://learn.microsoft.com/en-us/azure/foundry-classic/foundry-models/how-to/use-chat-reasoning
    *Confidence: Verified (MCP search 2026-02)*
 
 4. **Azure OpenAI function calling support**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/function-calling
+   https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/function-calling
    *Confidence: Verified (MCP search 2026-02)*
 
 5. **GPT-5 prompting guide (OpenAI)**

skills/ms-ai-advisor/references/prompt-engineering/regulatory-and-compliance-prompting.md

@@ -860,7 +860,7 @@ Før produksjonsdeploy, gjennomfør en 2-dagers compliance sprint:
 ### Microsoft Official Documentation
 
 1. **Data, privacy, and security for Azure OpenAI** (februar 2026)
-   https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/data-privacy
+   https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/data-privacy
    → Autoritativ kilde for data processing, abuse monitoring, residency
 
 2. **Govern AI apps and data for regulatory compliance** (februar 2026)
@@ -868,7 +868,7 @@ Før produksjonsdeploy, gjennomfør en 2-dagers compliance sprint:
    → Compliance Manager, Purview integration, EU AI Act readiness
 
 3. **Azure OpenAI Content Filtering** (februar 2026)
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter
+   https://learn.microsoft.com/en-us/azure/foundry-classic/foundry-models/concepts/content-filter
    → Content Safety API, thresholds, custom policies
 
 4. **Azure Data Residency** (februar 2026)

skills/ms-ai-advisor/references/prompt-engineering/role-playing-and-persona-techniques.md

@@ -666,22 +666,22 @@ If uncertain, explain limitations.
 
 **Microsoft Learn (offisielle kilder):**
 
-1. [System message design - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/advanced-prompt-engineering)
+1. [System message design - Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/advanced-prompt-engineering)
    *Komplett guide til system message design, key concepts, og best practices*
 
-2. [Safety system messages - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message)
+2. [Safety system messages - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message)
    *Authoring techniques, safety components, og testing strategies*
 
-3. [Prompt engineering techniques - Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering)
+3. [Prompt engineering techniques - Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering)
    *Bredere prompt-veiledning inkludert few-shot og token efficiency*
 
 4. [Use prompts in Copilot Studio](https://learn.microsoft.com/en-us/microsoft-copilot-studio/nlu-prompt-node) (Re-verified MCP 2026-04)
    *Prompt editor features: natural language creation, template library, model selection (Azure OpenAI/Foundry), temperature, knowledge retrieval, code interpreter. Prompt-nivå: agent-tool, topic-node, agent flow-node.*
 
-5. [Azure OpenAI On Your Data - Best practices](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data)
+5. [Azure OpenAI On Your Data - Best practices](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data)
    *System message bruk i RAG-scenarier*
 
-6. [Responsible AI practices for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/overview)
+6. [Responsible AI practices for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/overview)
    *Metaprompt tuning som mitigation strategy*
 
 **Code samples verifisert:**

skills/ms-ai-advisor/references/prompt-engineering/structured-output-formatting.md

@@ -420,10 +420,10 @@ Krever Azure OpenAI-ressurs med støttet modell (se over). Ingen spesiell lisens
 
 | URL | Tema | Konfidensnivå |
 |-----|------|---------------|
-| [Structured Outputs Guide](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/structured-outputs) | Hovedguide, API-eksempler, schema-begrensninger | **Verified** (2026-02) |
-| [JSON Mode Guide](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/json-mode) | JSON Mode (legacy), sammenlikning med structured outputs | **Verified** (2026-02) |
-| [API Reference (v1)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/latest) | REST API-detaljer, response_format konfigurasjon | **Verified** (2026-02) |
-| [Prompt Engineering Guide](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering) | Output structure best practices | **Verified** (2026-02) |
+| [Structured Outputs Guide](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/structured-outputs) | Hovedguide, API-eksempler, schema-begrensninger | **Verified** (2026-02) |
+| [JSON Mode Guide](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/json-mode) | JSON Mode (legacy), sammenlikning med structured outputs | **Verified** (2026-02) |
+| [API Reference (v1)](https://learn.microsoft.com/en-us/azure/foundry/openai/latest) | REST API-detaljer, response_format konfigurasjon | **Verified** (2026-02) |
+| [Prompt Engineering Guide](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering) | Output structure best practices | **Verified** (2026-02) |
 
 ### Azure OpenAI API-versjon
 - **Introduced:** `2024-08-01-preview`

skills/ms-ai-advisor/references/prompt-engineering/system-message-design-patterns.md

@@ -340,11 +340,11 @@ For store organisasjoner med mange AI-assistenter:
 ## Kilder og verifisering
 
 **Verified (fra Microsoft Learn MCP):**
-- System message design concepts: [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/advanced-prompt-engineering](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/advanced-prompt-engineering)
-- Prompt engineering techniques: [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering)
-- Safety system messages: [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message)
-- Code samples (Python SDK): [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chatgpt](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/chatgpt)
-- Azure OpenAI On Your Data best practices: [https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data)
+- System message design concepts: [https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/advanced-prompt-engineering](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/advanced-prompt-engineering)
+- Prompt engineering techniques: [https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering)
+- Safety system messages: [https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message)
+- Code samples (Python SDK): [https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/chatgpt](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/chatgpt)
+- Azure OpenAI On Your Data best practices: [https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data)
 
 **Baseline (modellkunnskap):**
 - EU AI Act compliance patterns (February 2026)

skills/ms-ai-advisor/references/prompt-engineering/temperature-sampling-and-parameters.md

@@ -559,13 +559,13 @@ for config in test_configs:
 ## Kilder og verifisering
 
 ### Microsoft Learn dokumentasjon
-1. [Prompt engineering techniques — Temperature and Top_p parameters](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering#temperature-and-top_p-parameters)
-2. [Azure OpenAI REST API reference — Completions](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/reference#completions)
-3. [Reproducible output with seed parameter](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/reproducible-output)
-4. [Model Router limitations (o-series)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/model-router#use-model-router-in-chats)
+1. [Prompt engineering techniques — Temperature and Top_p parameters](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/prompt-engineering#temperature-and-top_p-parameters)
+2. [Azure OpenAI REST API reference — Completions](https://learn.microsoft.com/en-us/azure/foundry/openai/reference#completions)
+3. [Reproducible output with seed parameter](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/reproducible-output)
+4. [Model Router limitations (o-series)](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/model-router#use-model-router-in-chats)
 
 ### Code samples
-5. [Azure OpenAI Python SDK — Chat Completions](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/supported-languages?pivots=programming-language-python#chat)
+5. [Azure OpenAI Python SDK — Chat Completions](https://learn.microsoft.com/en-us/azure/foundry/openai/supported-languages?pivots=programming-language-python#chat)
 6. [Semantic Kernel — OpenAIPromptExecutionSettings](https://learn.microsoft.com/en-us/dotnet/api/microsoft.semantickernel.connectors.openai.openaipromptexecutionsettings)
 
 ### Validert dato

skills/ms-ai-advisor/references/prompt-engineering/token-optimization-and-efficiency.md

@@ -583,10 +583,10 @@ Break-even requests/måned: $1,224 / $0.00036 = 3.4M requests
 ## Kilder og verifisering
 
 **Offisiell Microsoft-dokumentasjon:**
-1. [Prompt caching for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/prompt-caching)
-2. [Plan and manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs)
-3. [Performance and latency optimization](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/latency)
-4. [Batch API for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch)
+1. [Prompt caching for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/prompt-caching)
+2. [Plan and manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs)
+3. [Performance and latency optimization](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/latency)
+4. [Batch API for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/batch)
 5. [Azure OpenAI pricing](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/)
 
 **Verifisert:** Februar 2026 via microsoft-learn MCP-server

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)

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)**

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)

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**

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**

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

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)

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
 

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
 
 ---
 

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
 

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**

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"
 

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)
 

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
 

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
 

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**

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
 

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

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)
 

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
 

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 |

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

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
 
 ---

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**

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
 
 ---
 

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)
 

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/)

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)
 
 ---

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**

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)
 

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

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
 

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
 

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)

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) |
 

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) |

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**
 

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*

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)

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**
 

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** |

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
 

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) |

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)
 

skills/ms-ai-governance/references/monitoring-observability/compliance-monitoring-ai-governance.md

@@ -478,13 +478,13 @@ AppMetrics
 
 **Azure Policy & monitoring:**
 - [Azure Policy Regulatory Compliance controls for Azure AI Search](https://learn.microsoft.com/en-us/azure/search/security-controls-policy) — Verified 2026-02
-- [Control AI model deployment with built-in policies in Microsoft Foundry portal](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/built-in-policy-model-deployment) — Verified 2026-02
+- [Control AI model deployment with built-in policies in Microsoft Foundry portal](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/built-in-policy-model-deployment) — Verified 2026-02
 - [AI gateway in Azure API Management (Observability and governance)](https://learn.microsoft.com/en-us/azure/api-management/genai-gateway-capabilities#observability-and-governance) — Verified 2026-02
 
 **Security & observability:**
 - [Assess your organization's AI risk with Microsoft Security Dashboard for AI (Preview)](https://learn.microsoft.com/en-us/security/security-for-ai/security-dashboard-for-ai) — Verified 2026-02
 - [Governance and security for AI agents across the organization](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/ai-agents/governance-security-across-organization) — Verified 2026-02
-- [Monitor Azure OpenAI (Dashboards)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — Verified 2026-02
+- [Monitor Azure OpenAI (Dashboards)](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) — Verified 2026-02
 
 ### Konfidensnivå per seksjon
 

skills/ms-ai-governance/references/monitoring-observability/cost-monitoring-cost-attribution.md

@@ -439,7 +439,7 @@ if ($metrics.Data.Total -eq 0) {
 ### Kilder (Microsoft Learn)
 
 1. **Plan to 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
    *Konfidensgrad: Verified* – Komplett guide for cost management (budgets, alerts, export)
 
 2. **Azure OpenAI in Foundry Models gateway monitoring** *(Verified MCP 2026-04)*
@@ -455,7 +455,7 @@ if ($metrics.Data.Total -eq 0) {
    *Konfidensgrad: Verified* – Best practices for TPM/RPM monitoring, commitment billing
 
 5. **Plan and manage costs for Azure AI Foundry**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/manage-costs
+   https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs
    *Konfidensgrad: Verified* – Marketplace models, fine-tuning costs, HTTP error billing
 
 6. **Azure Cost Management API (Python SDK)**

skills/ms-ai-governance/references/monitoring-observability/custom-dashboards-ai-operations.md

@@ -483,7 +483,7 @@ Når kunden spør om dashboards for AI operations:
 ### Microsoft Learn
 - [Azure Workbooks overview](https://learn.microsoft.com/en-us/azure/azure-monitor/visualize/workbooks-overview)
 - [Create an Azure AI Foundry dashboard](https://learn.microsoft.com/en-us/azure/managed-grafana/azure-ai-foundry-dashboard)
-- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai)
+- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai)
 - [Workbooks programmatic management](https://learn.microsoft.com/en-us/azure/azure-monitor/visualize/workbooks-automate) *(Verified MCP 2026-04)* — ARM/Bicep deployment, RBAC (Monitoring Contributor for redigering, Monitoring Reader for visning), `microsoft.insights/workbooks/write` for custom roles
 - [Power BI + Azure Monitor](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/log-powerbi)
 

skills/ms-ai-governance/references/monitoring-observability/endpoint-health-and-capacity-planning.md

@@ -587,19 +587,19 @@ az role assignment create \
 ### Microsoft Learn (Verified via MCP)
 
 1. **Monitor Azure OpenAI:**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai
    *Confidence: Verified* — Komplett guide til diagnostics, metrics, alerts, og KQL-queries
 
 2. **Manage Azure OpenAI quota:**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/quota
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/quota
    *Confidence: Verified* — TPM/RPM-allokering, quota requests, 429-feilhåndtering
 
 3. **Azure OpenAI 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
    *Confidence: Verified* — Rate limits per modell, Usage tiers, regional constraints
 
 4. **Dynamic quota (Preview):**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/dynamic-quota
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/dynamic-quota
    *Confidence: Verified* — Opportunistic burst-kapasitet for Standard deployments
 
 5. **Supported metrics for Microsoft.CognitiveServices/accounts:**

skills/ms-ai-governance/references/monitoring-observability/log-analytics-kql-ai-queries.md

@@ -723,7 +723,7 @@ AzureDiagnostics
 
 - **KQL Quick Reference:** [learn.microsoft.com/kusto/query/kql-quick-reference](https://learn.microsoft.com/en-us/kusto/query/kql-quick-reference)
 - **Azure Monitor KQL Samples:** [learn.microsoft.com/azure/azure-monitor/logs/queries](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/queries)
-- **Azure OpenAI Monitoring:** [learn.microsoft.com/azure/ai-foundry/openai/how-to/monitor-openai](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai)
+- **Azure OpenAI Monitoring:** [learn.microsoft.com/azure/foundry-classic/openai/how-to/monitor-openai](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai)
 - **Optimize Log Queries:** [learn.microsoft.com/azure/azure-monitor/logs/query-optimization](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/query-optimization)
 
 ## Nøkkelinnsikter
@@ -743,7 +743,7 @@ AzureDiagnostics
 
 ## Referanser
 
-- Microsoft Learn: [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai)
+- Microsoft Learn: [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai)
 - Microsoft Learn: [Get started with log queries in Azure Monitor](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/get-started-queries)
 - Microsoft Learn: [Optimize log queries in Azure Monitor](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/query-optimization) *(Verified MCP 2026-04)*
 - Microsoft Learn: [Configure diagnostic logging for Azure AI Search](https://learn.microsoft.com/en-us/azure/search/search-monitor-enable-logging)

skills/ms-ai-governance/references/monitoring-observability/model-performance-drift-detection.md

@@ -377,8 +377,8 @@ Model monitoring er inkludert i Azure Machine Learning workspace, men du betaler
 - [Azure Machine Learning model monitoring (concept)](https://learn.microsoft.com/en-us/azure/machine-learning/concept-model-monitoring?view=azureml-api-2) — **Verified** (fetched 2026-02)
 - [Monitor performance of models deployed to production](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-model-performance?view=azureml-api-2) — **Verified** (fetched 2026-02)
 - [Data drift monitoring (legacy, retiring)](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-datasets?view=azureml-api-1) — **Verified** (fetched 2026-02, kontext: migrering til Model Monitor)
-- [Evaluate generative AI models (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — **Verified** (fetched 2026-02)
-- [Observability in generative AI (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability?view=foundry-classic) — **Verified** (fetched 2026-02)
+- [Evaluate generative AI models (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluate-generative-ai-app?view=foundry-classic) — **Verified** (fetched 2026-02)
+- [Observability in generative AI (Azure AI Foundry)](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability?view=foundry-classic) — **Verified** (fetched 2026-02)
 - [Test and evaluate AI workloads on Azure](https://learn.microsoft.com/en-us/azure/well-architected/ai/test) — **Verified** (fetched 2026-02)
 
 ### Baseline (Model knowledge)

skills/ms-ai-governance/references/monitoring-observability/real-time-streaming-monitoring.md

@@ -525,7 +525,7 @@ Real-Time Dashboard er IKKE erstatning for data warehouse. Bruk for operational
    **Confidence:** Verified (Feb 2026) - Real-time architecture patterns
 
 7. **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 (Feb 2026) - AI Foundry monitoring integration
 
 8. **Implement advanced monitoring for Azure OpenAI in Foundry Models through a gateway**

skills/ms-ai-governance/references/monitoring-observability/response-quality-metrics-rag.md

@@ -591,14 +591,14 @@ PTU equivalent: ~300 PTUs @ $6/PTU = $1800/måned
 
 ### Microsoft Learn (Verified via MCP)
 
-1. [Observability in generative AI - What are evaluators?](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability#what-are-evaluators) — RAG evaluators (Retrieval, Groundedness, Relevance, Response Completeness)
-2. [Retrieval-Augmented Generation (RAG) evaluators](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/evaluation-evaluators/rag-evaluators) — Detaljert dokumentasjon for alle RAG-evaluatorer, input/output formats
+1. [Observability in generative AI - What are evaluators?](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability#what-are-evaluators) — RAG evaluators (Retrieval, Groundedness, Relevance, Response Completeness)
+2. [Retrieval-Augmented Generation (RAG) evaluators](https://learn.microsoft.com/en-us/azure/foundry/concepts/evaluation-evaluators/rag-evaluators) — Detaljert dokumentasjon for alle RAG-evaluatorer, input/output formats
 3. [Large language model end-to-end evaluation](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-llm-evaluation-phase) — Groundedness, completeness, utilization, relevance, correctness metrics
-4. [Evaluate generative AI models and applications](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluate-generative-ai-app) — Foundry portal evaluation workflow, testing criteria configuration
-5. [Submit a batch run and evaluate a flow](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/flow-bulk-test-evaluation) — Built-in evaluation methods (QnA Groundedness, Relevance, Coherence)
+4. [Evaluate generative AI models and applications](https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluate-generative-ai-app) — Foundry portal evaluation workflow, testing criteria configuration
+5. [Submit a batch run and evaluate a flow](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/flow-bulk-test-evaluation) — Built-in evaluation methods (QnA Groundedness, Relevance, Coherence)
 6. [Evaluation of RAG performance basics](https://learn.microsoft.com/en-us/fabric/data-science/tutorial-evaluate-rag-performance) — AI-assisted metrics (groundedness, relevance, similarity), top-N retrieval rate
-7. [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — Azure Monitor integration, KQL queries, diagnostic settings
-8. [Use Risks & Safety monitoring](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/risks-safety-monitor) — Content filtering metrics, severity distribution
+7. [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) — Azure Monitor integration, KQL queries, diagnostic settings
+8. [Use Risks & Safety monitoring](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/risks-safety-monitor) — Content filtering metrics, severity distribution
 9. [Azure AI Evaluation SDK - Python samples](https://github.com/Azure-Samples/azureai-samples/blob/main/scenarios/evaluate/) — Code examples for groundedness, relevance evaluators
 
 ### Code samples (Verified via MCP)

skills/ms-ai-governance/references/monitoring-observability/security-and-audit-logging-ai.md

@@ -385,8 +385,8 @@ Ingen ekstra lisenser kreves for audit logging — funksjonen er inkludert i Azu
 | Kilde | URL | Konfidensnivå |
 |-------|-----|---------------|
 | **Enable diagnostic logging for Azure AI services** | https://learn.microsoft.com/en-us/azure/ai-services/diagnostic-logging | ✅ Verified |
-| **Monitor Azure OpenAI** | https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai | ✅ Verified |
-| **Azure security baseline for Azure OpenAI** | https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/azure-openai-security-baseline | ✅ Verified — **OBS:** Basert på MCSB v1.0 (kan inneholde utdatert veiledning). Produktet refereres nå som "Foundry Tools" i baseline-dokumentet. Siste veiledning: [Azure OpenAI docs](https://learn.microsoft.com/en-us/azure/ai-foundry/). *(Verified MCP 2026-04)* |
+| **Monitor Azure OpenAI** | https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai | ✅ Verified |
+| **Azure security baseline for Azure OpenAI** | https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/azure-openai-security-baseline | ✅ Verified — **OBS:** Basert på MCSB v1.0 (kan inneholde utdatert veiledning). Produktet refereres nå som "Foundry Tools" i baseline-dokumentet. Siste veiledning: [Azure OpenAI docs](https://learn.microsoft.com/en-us/azure/foundry/). *(Verified MCP 2026-04)* |
 | **Azure security baseline for Microsoft Foundry** | https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/azure-ai-foundry-security-baseline | ✅ Verified — **OBS:** Tjenesten er omdøpt til "Microsoft Foundry" i baseline-dokumentet. Basert på MCSB v1.0. Viktige avvik: Customer Lockbox **ikke støttet** for Foundry, lokal autentisering til data plane **ikke støttet** (positivt for sikkerhet), DLP/sensitive data discovery **ikke støttet** nativt. *(Verified MCP 2026-04)* |
 | **Microsoft cloud security benchmark: Logging and threat detection** | https://learn.microsoft.com/en-us/security/benchmark/azure/mcsb-logging-threat-detection | ✅ Verified |
 | **Artificial Intelligence Security (AI-6: Establish monitoring and detection)** | https://learn.microsoft.com/en-us/security/benchmark/azure/mcsb-v2-artificial-intelligence-security | ✅ Verified |

skills/ms-ai-governance/references/monitoring-observability/sla-monitoring-ai-services.md

@@ -351,11 +351,11 @@ Metric Alert
 ### Microsoft Learn (Verified via MCP)
 
 1. **Monitor Azure OpenAI**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai
    *Confidence: Verified* — Detaljert guide til Azure Monitor-integrasjon for OpenAI.
 
 2. **Azure OpenAI monitoring data reference**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/monitor-openai-reference
+   https://learn.microsoft.com/en-us/azure/foundry/openai/monitor-openai-reference
    *Confidence: Verified* — Fullstendig liste over metrics (inkl. `ModelAvailabilityRate`).
 
 3. **Monitoring and diagnostics guidance**
@@ -363,7 +363,7 @@ Metric Alert
    *Confidence: Verified* — SLA monitoring best practices (generell Azure-arkitektur). Dekker: tilgjengelighetssporing, ytelsesovervåkning, SLA-etterlevelse, sikkerhet/personvern, regulatorisk audit, trend-deteksjon. Brukes i AI-kontekst for å sikre end-to-end synlighet i distribuerte AI-systemer. *(Verified MCP 2026-04)*
 
 4. **Azure OpenAI FAQ - SLA**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/faq#what-are-the-slas-service-level-agreements-in-azure-openai
+   https://learn.microsoft.com/en-us/azure/foundry-classic/openai/faq#what-are-the-slas-service-level-agreements-in-azure-openai
    *Confidence: Verified* — Bekreftelse av 99.9% Availability SLA + Latency SLA for PTU.
 
 5. **Supported metrics for Microsoft.CognitiveServices/accounts**

skills/ms-ai-governance/references/monitoring-observability/token-usage-tracking-attribution.md

@@ -568,11 +568,11 @@ Owner: <email>
 
 ## Kilder (Microsoft Learn)
 
-1. [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — Official monitoring guide
+1. [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) — Official monitoring guide
 2. [Implement advanced monitoring for Azure OpenAI in Foundry Models through a gateway](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-monitoring) *(Verified MCP 2026-04)* — Gateway patterns for usage tracking. Ny brukscase dokumentert: audit av model inputs/outputs for threat detection og data exfiltration detection. Merk: gateway monitoring kan bli single point of failure — vurder redundans.
-3. [Plan to manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs) — Cost management strategies
-4. [Token usage estimation for Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data#token-usage-estimation-for-azure-openai-on-your-data) — RAG-specific token calculations
-5. [Understanding costs associated with PTU](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/provisioned-throughput-onboarding) — PTU billing model
+3. [Plan to manage costs for Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs) — Cost management strategies
+4. [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) — RAG-specific token calculations
+5. [Understanding costs associated with PTU](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/provisioned-throughput-billing) — PTU billing model
 6. [Application design for AI workloads](https://learn.microsoft.com/en-us/azure/well-architected/ai/application-design#consider-nonfunctional-requirements) — Cost and chargeback scenarios
 7. [Architecture strategies for cost data](https://learn.microsoft.com/en-us/azure/well-architected/cost-optimization/collect-review-cost-data#generate-cost-reports) — Chargeback vs. showback
 

skills/ms-ai-governance/references/norwegian-public-sector-governance/copyright-ai-training-data-norway.md

@@ -142,7 +142,7 @@ Kunden må ha implementert alle mitigations (tiltak) som kreves i Azure OpenAI-d
 For å opprettholde CCC-dekning må kunder implementere følgende universelle mitigations:
 
 **1. Metaprompt (effektiv fra 1. desember 2023):**
-Kundens løsning må inkludere en metaprompt som instruerer modellen til å forhindre opphavsrettsbrudd i output. Eksempel på anbefalt metaprompt finnes i Microsoft Learn: "To Avoid Copyright Infringements" i [System message framework and template recommendations for Large Language Models (LLMs)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message).
+Kundens løsning må inkludere en metaprompt som instruerer modellen til å forhindre opphavsrettsbrudd i output. Eksempel på anbefalt metaprompt finnes i Microsoft Learn: "To Avoid Copyright Infringements" i [System message framework and template recommendations for Large Language Models (LLMs)](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message).
 
 **2. Testing and Evaluation Report (effektiv fra 1. desember 2023):**
 Kundens løsning må ha vært gjenstand for evalueringer (f.eks. guided red teaming, systematisk måling, eller annen ekvivalent tilnærming) ved hjelp av tester designet for å oppdage output av tredjepartsinnhold. Betydelig løpende reproduksjon av tredjepartsinnhold oppdaget gjennom evaluering må adresseres. Rapporten over resultater og tiltak må oppbevares av kunden og gjøres tilgjengelig for Microsoft i tilfelle krav.
@@ -243,11 +243,11 @@ Når du veileder norsk offentlig sektor om AI og opphavsrett, vurder disse spør
 - [Commission launches consultation on protocols for reserving rights from text and data mining under the AI Act and the GPAI Code of Practice](https://digital-strategy.ec.europa.eu/en/consultations/commission-launches-consultation-protocols-reserving-rights-text-and-data-mining-under-ai-act-and)
 
 ### Microsoft Learn-kilder
-- [Customer Copyright Commitment Required Mitigations | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/customer-copyright-commitment?view=foundry-classic)
-- [Data, privacy, and security for Azure Direct Models in Microsoft Foundry | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/data-privacy?view=foundry-classic)
-- [Transparency note for Azure OpenAI | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note?view=foundry-classic)
-- [Azure OpenAI frequently asked questions | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/faq?view=foundry-classic)
-- [System message framework and template recommendations for LLMs | Microsoft Learn](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/system-message)
+- [Customer Copyright Commitment Required Mitigations | Microsoft Learn](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/customer-copyright-commitment?view=foundry-classic)
+- [Data, privacy, and security for Azure Direct Models in Microsoft Foundry | Microsoft Learn](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/data-privacy?view=foundry-classic)
+- [Transparency note for Azure OpenAI | Microsoft Learn](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note?view=foundry-classic)
+- [Azure OpenAI frequently asked questions | Microsoft Learn](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/faq?view=foundry-classic)
+- [System message framework and template recommendations for LLMs | Microsoft Learn](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/system-message)
 
 ---
 

skills/ms-ai-governance/references/responsible-ai/ai-impact-assessment-framework.md

@@ -616,7 +616,7 @@ Purview SDK-integrasjon gir:
    - Status: Azure ML GA feature
 
 6. **Azure AI Foundry Evaluation**
-   - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/evaluation-github-action
+   - URL: https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluation-github-action
    - Status: Azure AI Foundry GA
 
 7. **Microsoft Purview AI Risk Management**

skills/ms-ai-governance/references/responsible-ai/ai-risk-taxonomy-classification.md

@@ -420,7 +420,7 @@ Anbefal denne kombinasjonen:
    - Innhold: Cross-product risk monitoring, AI inventory
 
 5. **Default Guidelines & controls policies (Azure AI Foundry)**
-   - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/default-safety-policies
+   - URL: https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/default-safety-policies
    - Hentet: 2026-02-04
    - Innhold: Content filtering categories, severity levels, default thresholds
 

skills/ms-ai-governance/references/responsible-ai/algorithmic-accountability-auditability.md

@@ -516,7 +516,7 @@ registered_model = ml_client.models.create_or_update(model)
    (Assign unique identities, maintain agent inventory, centralize logging, track and allocate costs)
 
 5. **Trace and observe AI agents in Microsoft Foundry**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/trace-agents-sdk?view=foundry-classic
+   https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/trace-agents-sdk?view=foundry-classic
    (OpenTelemetry tracing, Application Insights integration, Azure Monitor exporter)
 
 6. **Microsoft Purview data security and compliance protections for generative AI apps**

skills/ms-ai-governance/references/responsible-ai/bias-detection-mitigation-strategies.md

@@ -937,7 +937,7 @@ Risikokategori (EU AI Act)?
    Verifisert: 2026-02-03 | Status: GA | Confidence: ✅ High
 
 6. **Content filter severity levels**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-severity-levels
+   https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-severity-levels
    Verifisert: 2026-02-03 | Status: GA | Confidence: ✅ High
 
 7. **Monitor fairness and bias (Databricks)**

skills/ms-ai-governance/references/responsible-ai/content-safety-implementation.md

@@ -280,7 +280,7 @@ Azure AI Content Safety har PII-detection for completions:
 | **Record-keeping** | Retain logs i 6+ år (Azure Log Analytics long-term retention) |
 
 **Transparency Note:**
-Microsoft publiserer [Transparency Note for Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/content-safety/transparency-note) som dekker:
+Microsoft publiserer [Transparency Note for Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/content-safety/transparency-note) som dekker:
 - System capabilities and limitations
 - Training data og known biases
 - Best practices for deployment
@@ -464,22 +464,22 @@ Scenario: 1 million samtaler/måned, gjennomsnitt 2 meldinger per samtale = 2M t
 1. [What is Azure AI Content Safety?](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/overview)
    *Confidence: High* — Oversikt over features, pricing tiers, region availability, service limits
 
-2. [Content filtering overview (Azure OpenAI)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter)
+2. [Content filtering overview (Azure OpenAI)](https://learn.microsoft.com/en-us/azure/foundry-classic/foundry-models/concepts/content-filter)
    *Confidence: High* — Filter categories, severity levels, scenario details for API response behavior
 
 3. [Harm categories in Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/harm-categories)
    *Confidence: High* — Detaljert beskrivelse av severity levels 0-7 per kategori (hate, sexual, violence, self-harm)
 
-4. [Data, privacy, and security for Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/content-safety/data-privacy)
+4. [Data, privacy, and security for Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/content-safety/data-privacy)
    *Confidence: High* — Data residency, encryption at rest, customer controls, GDPR compliance statements
 
 5. [Custom categories (preview)](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/custom-categories)
    *Confidence: Medium* — Preview feature, API-detaljer kan endre seg før GA
 
-6. [Transparency note: Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/content-safety/transparency-note)
+6. [Transparency note: Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/content-safety/transparency-note)
    *Confidence: High* — System capabilities, intended uses, limitations, best practices
 
-7. [Default Guidelines & controls policies (Azure OpenAI)](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/default-safety-policies)
+7. [Default Guidelines & controls policies (Azure OpenAI)](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/default-safety-policies)
    *Confidence: High* — Default severity thresholds for text/image models, table of blocked categories
 
 8. [Azure AI Content Safety Quickstart (C# code samples)](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/quickstart-text?pivots=programming-language-csharp)
@@ -488,7 +488,7 @@ Scenario: 1 million samtaler/måned, gjennomsnitt 2 meldinger per samtale = 2M t
 9. [Mitigate false results in Azure AI Content Safety](https://learn.microsoft.com/en-us/azure/ai-services/content-safety/how-to/improve-performance)
    *Confidence: High* — Best practices for severity tuning, custom categories, blocklists
 
-10. [Content Safety in the Microsoft Foundry portal](https://learn.microsoft.com/en-us/azure/ai-foundry/ai-services/content-safety-overview)
+10. [Content Safety in the Microsoft Foundry portal](https://learn.microsoft.com/en-us/azure/foundry-classic/ai-services/content-safety-overview)
     *Confidence: High* — Beskrivelse av Content Safety Studio features, Try it out workflow
 
 **Baseline (modellkunnskap, ikke verifisert mot ferske kilder):**

skills/ms-ai-governance/references/responsible-ai/continuous-improvement-feedback-loops.md

@@ -48,7 +48,7 @@ Microsoft implementerer feedback loops gjennom hele AI-livssyklusen – fra utvi
 - Error logs og exception traces
 - User feedback (thumbs up/down, ratings)
 
-**Confidence:** Verified – [MLflow Tracing](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/), [Azure Monitor](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability)
+**Confidence:** Verified – [MLflow Tracing](https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/), [Azure Monitor](https://learn.microsoft.com/en-us/azure/foundry/concepts/observability)
 
 ### 2. Automated Quality Monitoring
 
@@ -69,7 +69,7 @@ Microsoft bruker automated scorers (LLM judges) for kontinuerlig kvalitetsvurder
 - Automated alerts ved threshold violations
 - Integration med Azure AI Foundry evaluation tools
 
-**Confidence:** Verified – [Generation Quality Monitoring](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/monitor-quality-safety?view=foundry-classic)
+**Confidence:** Verified – [Generation Quality Monitoring](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/monitor-quality-safety?view=foundry-classic)
 
 ### 3. Human Feedback Integration
 
@@ -258,7 +258,7 @@ model_monitor = MonitorSchedule(
 )
 ```
 
-**Confidence:** Verified – [Azure AI Foundry Monitoring](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/monitor-quality-safety?view=foundry-classic)
+**Confidence:** Verified – [Azure AI Foundry Monitoring](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/monitor-quality-safety?view=foundry-classic)
 
 ### MLflow on Azure Databricks
 
@@ -531,7 +531,7 @@ Models, prompts, eval datasets, scorers – full reproducibility er non-negotiab
    - Key content: 10-step feedback loop, human-aligned metrics, production monitoring
 
 2. **Azure AI Foundry Production Monitoring**
-   - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/monitor-quality-safety?view=foundry-classic
+   - URL: https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/monitor-quality-safety?view=foundry-classic
    - Key content: Continuous evaluation, scorers, threshold configuration
 
 3. **AI Builder Feedback Loop**
@@ -571,7 +571,7 @@ Models, prompts, eval datasets, scorers – full reproducibility er non-negotiab
     - Key content: Feedback mechanisms, bias monitoring, iterative updates
 
 12. **Azure AI Foundry Observability Concepts**
-    - URL: https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability
+    - URL: https://learn.microsoft.com/en-us/azure/foundry/concepts/observability
     - Key content: Tracing, monitoring features, model performance tracking
 
 **Code samples (Verified):**

skills/ms-ai-governance/references/responsible-ai/gdpr-compliance-ai-systems.md

@@ -537,7 +537,7 @@ Norge implementerer GDPR gjennom personopplysningsloven. Datatilsynet er tilsyns
    *How to handle access, rectify, erase, restrict, portability, object requests*
 
 6. **Data, privacy, and security for Azure OpenAI**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/data-privacy
+   https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/data-privacy
    *No training on customer data, no sharing with OpenAI, encryption, CMK support*
 
 7. **Manage personal data in Azure Monitor Logs**

skills/ms-ai-governance/references/responsible-ai/human-in-the-loop-oversight.md

@@ -790,7 +790,7 @@ For offentlig sektor i Norge:
 3. [Power Automate - Multistage and AI approvals](https://learn.microsoft.com/en-us/microsoft-copilot-studio/flows-advanced-approvals) — Power Platform approvals
 4. [FAQ for AI Approvals](https://learn.microsoft.com/en-us/microsoft-copilot-studio/faqs-ai-approvals) — Best practices og limitations
 5. [Copilot Studio - Topic escalation analysis](https://learn.microsoft.com/en-us/microsoft-copilot-studio/guidance/deflection-topic-escalation-analysis) — Escalation patterns
-6. [Azure AI Agent Service - Transparency Note](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/agents/transparency-note) — Real-time oversight guidance
+6. [Azure AI Agent Service - Transparency Note](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/agents/transparency-note) — Real-time oversight guidance
 7. [Durable Agent Features - HITL workflows](https://learn.microsoft.com/en-us/agent-framework/user-guide/agents/agent-types/durable-agent/features) — Durable Functions patterns
 8. [Responsible AI in Azure workloads](https://learn.microsoft.com/en-us/azure/well-architected/ai/responsible-ai) — Escape hatches og human-in-the-loop checkpoints
 9. [Catalog Enrichment Agent - Responsible AI FAQ](https://learn.microsoft.com/en-us/industry/retail/catalog-enrichment-agent/faqs-catalog-enrichment-agent) — Human-in-the-loop implementation example

skills/ms-ai-governance/references/responsible-ai/model-explainability-interpretability.md

@@ -530,7 +530,7 @@ SLUTT: Dokumenter valg i ADR, implementer, valider med stakeholders
    *Confidence: Verified* - Alternative XAI-teknikk for .NET-utviklere
 
 7. **Azure OpenAI Transparency Note - Limitations**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note?view=foundry-classic#limitations
+   https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note?view=foundry-classic#limitations
    *Confidence: Verified* - Begrensninger i explainability for fine-tuned og reasoning models
 
 ### Ekstern dokumentasjon (Baseline knowledge)

skills/ms-ai-governance/references/responsible-ai/red-teaming-ai-models.md

@@ -247,7 +247,7 @@ steps:
 - Azure tool calls (✅ supported)
 - Function tool calls (❌ not supported)
 
-**Comprehensive tools list:** [Azure AI Foundry Tools](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/overview)
+**Comprehensive tools list:** [Azure AI Foundry Tools](https://learn.microsoft.com/en-us/azure/foundry-classic/agents/how-to/tools-classic/overview)
 
 ### Azure OpenAI Service
 
@@ -492,10 +492,10 @@ jobs:
 
 | Kilde | URL | Verifikasjonsdato |
 |-------|-----|-------------------|
-| **AI Red Teaming Agent (preview)** | https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/ai-red-teaming-agent | 2026-02-03 |
+| **AI Red Teaming Agent (preview)** | https://learn.microsoft.com/en-us/azure/foundry/concepts/ai-red-teaming-agent | 2026-02-03 |
 | **Microsoft Security Benchmark: AI-7 Continuous Red Teaming** | https://learn.microsoft.com/en-us/security/benchmark/azure/mcsb-v2-artificial-intelligence-security#ai-7-perform-continuous-ai-red-teaming | 2026-02-03 |
 | **AI Red Teaming Training Series** | https://learn.microsoft.com/en-us/security/ai-red-team/training | 2026-02-03 |
-| **Planning red teaming for LLMs** | https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/red-teaming | 2026-02-03 |
+| **Planning red teaming for LLMs** | https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/red-teaming | 2026-02-03 |
 | **Prompt Shields (Jailbreak detection)** | https://learn.microsoft.com/en-us/azure/ai-services/content-safety/concepts/jailbreak-detection | 2026-02-03 |
 
 ### Open-source verktøy

skills/ms-ai-governance/references/responsible-ai/responsible-ai-policy-development.md

@@ -227,7 +227,7 @@ Start: New AI initiative or capability?
 | **Content Safety** | Harmful content filtering (text, image, multimodal) | [Azure AI Content Safety](https://learn.microsoft.com/azure/ai-services/content-safety/) - konfigurerbare severity thresholds |
 | **Evaluation Tools** | Pre-deployment safety, hallucination, bias testing | [Foundry evaluation SDK](https://learn.microsoft.com/azure/ai-studio/) - integreres i CI/CD |
 | **Model Registry** | Versioning, approval workflows, provenance tracking | [Azure ML Model Registry](https://learn.microsoft.com/azure/machine-learning/concept-model-management-and-deployment) - RBAC-controlled |
-| **Monitoring** | Model drift, performance degradation, quality metrics | [Foundry Agent Service metrics](https://learn.microsoft.com/azure/ai-foundry/agents/how-to/metrics) - alert rules |
+| **Monitoring** | Model drift, performance degradation, quality metrics | [Foundry Agent Service metrics](https://learn.microsoft.com/azure/foundry/observability/how-to/how-to-monitor-agents-dashboard) - alert rules |
 | **Data Governance** | Data lineage, sensitivity labels, DLP policies | [Microsoft Purview integration](https://learn.microsoft.com/purview/ai-azure-services) |
 
 **Policy Implementation Example (Foundry):**

skills/ms-ai-governance/references/responsible-ai/stakeholder-communication-ai-decisions.md

@@ -804,7 +804,7 @@ Hvis noen av disse mangler: **IKKE deploy før de er på plass.** AI uten stakeh
    - Verifisert: 2026-02
 
 6. **Transparency note for Azure OpenAI**
-   - https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note?view=foundry-classic
+   - https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note?view=foundry-classic
    - Status: GA
    - Verifisert: 2026-02
 

skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md

@@ -380,7 +380,7 @@ rai_insights.save("rai_scorecard.pdf")
 - Content filter annotations → apps kan forklare hvorfor content ble blocked
 
 **Transparency Note URL:**
-https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note
+https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note
 
 ---
 
@@ -699,15 +699,15 @@ Return on investment: Transparency er billigere enn cleanup. Skal vi prioritere
 **Verified sources (MCP: microsoft-learn):**
 
 1. **Transparency note for Azure OpenAI**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/transparency-note
+   https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/openai/transparency-note
    (Status: Verified 2026-02 — Latest updates: o3/o4-mini, Deep Research system cards)
 
 2. **Transparency note for Azure AI Search**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/search/transparency-note
+   https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/search/transparency-note
    (Status: Verified 2026-02 — Recommendations for A/B testing, bias detection)
 
 3. **Transparency note for Document Intelligence**
-   https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/document-intelligence/transparency-note
+   https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/document-intelligence/transparency-note
    (Status: Verified 2026-02 — Limitations for prebuilt/custom models)
 
 4. **Responsible AI scorecard documentation**

skills/ms-ai-infrastructure/references/bcdr/ai-foundry-disaster-recovery-planning.md

@@ -482,10 +482,10 @@ Bruk Azure Chaos Studio for automatisert feilinjeksjon:
 
 ## Referanser
 
-- [High availability and resiliency for Microsoft Foundry projects and Agent Services](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/high-availability-resiliency)
-- [Foundry Agent Service disaster recovery](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/agent-service-disaster-recovery)
-- [Foundry Agent Service resource and data loss recovery](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/agent-service-operator-disaster-recovery)
-- [High availability and disaster recovery for hub projects](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/hub-disaster-recovery)
+- [High availability and resiliency for Microsoft Foundry projects and Agent Services](https://learn.microsoft.com/en-us/azure/foundry/how-to/high-availability-resiliency)
+- [Foundry Agent Service disaster recovery](https://learn.microsoft.com/en-us/azure/foundry/how-to/agent-service-disaster-recovery)
+- [Foundry Agent Service resource and data loss recovery](https://learn.microsoft.com/en-us/azure/foundry/how-to/agent-service-operator-disaster-recovery)
+- [High availability and disaster recovery for hub projects](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/hub-disaster-recovery)
 - [Azure security baseline for Azure AI Foundry - Backup and recovery](https://learn.microsoft.com/en-us/security/benchmark/azure/baselines/azure-ai-foundry-security-baseline#backup-and-recovery)
 - [Continuous backup with point-in-time restore in Azure Cosmos DB](https://learn.microsoft.com/en-us/azure/cosmos-db/continuous-backup-restore-introduction)
 

skills/ms-ai-infrastructure/references/bcdr/capacity-planning-dr-configurations.md

@@ -329,7 +329,7 @@ az capacity reservation create \
 - [Develop a disaster recovery plan — Optimize your recovery costs](https://learn.microsoft.com/en-us/azure/well-architected/design-guides/disaster-recovery#optimize-your-recovery-costs) — Kostnadsoptimalisering per tier
 - [Recovery strategy for active-passive (warm standby)](https://learn.microsoft.com/en-us/azure/well-architected/design-guides/disaster-recovery#recovery-strategy-for-active-passive-warm-standby) — Warm standby konfigurasjon
 - [Recovery strategy for active-active deployments](https://learn.microsoft.com/en-us/azure/well-architected/design-guides/disaster-recovery#recovery-strategy-for-active-active-deployments) — Active-active konfigurasjon
-- [BCDR considerations with Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/business-continuity-disaster-recovery) — OpenAI-spesifikk kapasitetsplanlegging
+- [BCDR considerations with Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/high-availability-resiliency) — OpenAI-spesifikk kapasitetsplanlegging
 - [Management recommendations for AI workloads on Azure IaaS](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/infrastructure/management) — AI-workload management
 - [Azure Site Recovery — Plan capacity and scaling](https://learn.microsoft.com/en-us/azure/site-recovery/site-recovery-plan-capacity-vmware) — Kapasitetsplanlegging
 

skills/ms-ai-infrastructure/references/bcdr/incident-response-ai-systems.md

@@ -305,7 +305,7 @@ Tiltak: [Hva gjøres for å forhindre gjentakelse]
 - [Microsoft Defender for AI Services](https://learn.microsoft.com/en-us/azure/defender-for-cloud/ai-threat-protection) — AI-spesifikk trusseloppdaging
 - [Azure Monitor alerts overview](https://learn.microsoft.com/en-us/azure/azure-monitor/alerts/alerts-overview) — Alert-rammeverk
 - [Microsoft Sentinel overview](https://learn.microsoft.com/en-us/azure/sentinel/overview) — SIEM/SOAR for sikkerhetshendelser
-- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — OpenAI-spesifikk monitoring
+- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) — OpenAI-spesifikk monitoring
 
 ## For Cosmo
 

skills/ms-ai-infrastructure/references/bcdr/monitoring-alerting-failover-detection.md

@@ -438,7 +438,7 @@ Azure Monitor Application Insights tilbyr nå dedikert støtte for AI-agenter vi
 
 ## Referanser
 
-- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/monitor-openai) — OpenAI monitoring og alerting
+- [Monitor Azure OpenAI](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/monitor-openai) — OpenAI monitoring og alerting
 - [Monitor Azure AI Search](https://learn.microsoft.com/en-us/azure/search/monitor-azure-cognitive-search) — AI Search monitoring
 - [Azure Monitor alerts overview](https://learn.microsoft.com/en-us/azure/azure-monitor/alerts/alerts-overview) — Alert-rammeverk *(Verified MCP 2026-04)* — Stateful vs. stateless alerts. **Simple Log Search Alerts** (GA) for per-row KQL evaluering — raskere varsling enn tradisjonelle log alerts. **Query-based metric alerts** for Prometheus/OTel (public preview). Alerts stored 30 dager. Fired instances er read-only. Alert processing rules for suppression ved planlagt vedlikehold. **Azure Monitor Baseline Alerts** (`aka.ms/amba`) for policy-basert alerting i skala via Azure Policy.
 - [Health modeling and observability of mission-critical workloads](https://learn.microsoft.com/en-us/azure/well-architected/mission-critical/mission-critical-health-modeling) — Health modeling