You are working inside the existing production repository for:
Your task is to AUDIT, RESEARCH, DESIGN, IMPLEMENT, INTERNALLY LINK, SEO-OPTIMIZE, VALIDATE AND COMPLETE a FULL MICROSOFT AZURE AI / ML / GENERATIVE AI / AGENTIC AI CONTENT CLUSTER across the existing site.
This must be implemented at the same level of depth and completeness as the existing AWS AI/ML + Amazon Bedrock + Amazon SageMaker cluster.
This is an END-TO-END IMPLEMENTATION TASK.
DO NOT stop at planning. DO NOT only produce recommendations. DO NOT ask me for confirmation between phases. DO NOT break existing pages. DO NOT remove existing URLs. DO NOT rename working routes. DO NOT duplicate existing search intent. DO NOT mass-generate thin pages.
The final result must create a connected search and conversion funnel:
HOME → TECHNOLOGIES → SERVICES → AZURE AI / MICROSOFT FOUNDRY HUB → AZURE OPENAI / FOUNDRY MODELS / AGENTS / AZURE ML / RAG / MLOPS / DATA / INFRASTRUCTURE → TECHNICAL SUBSERVICES → PRODUCTION / TROUBLESHOOTING / GUIDES / INTERVIEW → ROLE → COUNTRY → CITY → JOB SUPPORT / INTERVIEW SUPPORT / PROFILE POSITIONING / CANDIDATE MARKETING → WHATSAPP / CONTACT
Before creating pages:
- Inspect the entire repository.
- Inspect routes, components, templates, metadata utilities and content-generation patterns.
- Find all existing Azure pages.
- Find all existing Azure OpenAI pages.
- Find all Azure AI / ML / cloud / .NET Azure pages.
- Find existing AI/ML global pages.
- Find existing job-support pages.
- Find existing interview-support pages.
- Find country and city architecture.
- Find existing guide/blog/comparison pages.
- Find sitemap generation.
- Find robots.txt.
- Find llms.txt and llms-full.txt.
- Find JSON-LD implementation.
- Find breadcrumb implementation.
- Find homepage Technologies and Services sections.
- Find current CTA / WhatsApp handling.
- Find analytics / GTAG / tracking.
- Find duplicated or legacy Azure URLs.
- Build an inventory BEFORE adding content.
Classify every relevant URL as:
EXISTING — preserve EXISTING PARTIAL — minimally enhance MISSING — candidate for creation DUPLICATE INTENT — skip LEGACY — preserve but connect/migrate contextually DEPRECATED TECH CONTENT — update only where technically justified
This is an existing production site.
You MUST:
- preserve existing working routes
- preserve existing content unless technically incorrect
- preserve design
- preserve analytics
- preserve structured data
- preserve existing internal links
- preserve existing contact logic
- preserve sitemap logic
- preserve canonical behavior
- preserve SEO equity
Do NOT:
- delete pages
- rename existing URLs
- replace large existing pages unnecessarily
- create duplicate pages
- create duplicate slugs
- remove GTAG
- remove schema
- redesign the whole website
- rewrite unrelated clusters
Only make changes necessary to build the Azure AI cluster and connect it cleanly.
================================================== PHASE 1 — MANDATORY AUGUST 2026 MICROSOFT RESEARCH
Before writing ANY Azure AI content, research the latest official Microsoft/Azure information through August 2026.
Use primarily:
- learn.microsoft.com
- azure.microsoft.com
- Microsoft Foundry documentation
- Azure AI Search documentation
- Azure Machine Learning documentation
- Microsoft Foundry Agent Service documentation
- Microsoft Foundry Models documentation
- Microsoft Foundry release notes
- Azure What's New
- Microsoft architecture guidance
- official Microsoft blogs where required
Do not rely on stale 2024/2025 assumptions.
Verify:
CURRENT NAMES CURRENT GA/PREVIEW STATUS CURRENT API NAMES CURRENT MODEL NAMES CURRENT RETIREMENTS CURRENT MIGRATION PATHS CURRENT SDK NAMES CURRENT REGIONS CURRENT ARCHITECTURE
As of August 2026, verify and use current naming.
The cluster should primarily use:
Microsoft Foundry Foundry Models Foundry Agent Service Foundry Tools Foundry IQ Foundry Model Router Foundry Local Azure Machine Learning Azure AI Search Azure OpenAI in Foundry Models
Retain older search terms naturally where useful:
Azure AI Foundry Azure AI Studio Azure OpenAI Service Azure Cognitive Services Azure AI Services
BUT:
Do NOT present outdated names as the primary current architecture if Microsoft has replaced them.
Use wording such as:
“Microsoft Foundry (formerly Azure AI Foundry / Azure AI Studio)”
only where helpful for search and migration intent.
Verify these before writing:
-
Microsoft Foundry current platform architecture.
-
Foundry Agent Service:
- Responses API
- Agent Runtime
- prompt agents
- hosted agents
- conversations/items/responses
- agent versions
- tools
- web search
- file search
- memory
- code interpreter
- MCP
- custom functions
- A2A
- Toolbox
- authentication
- tracing
- evaluation
-
Foundry Models:
- model catalog
- OpenAI models
- Anthropic models
- xAI
- DeepSeek
- Meta models
- deployment types
- model routing
- model evaluation
-
Model Router:
- August 2026 availability
- 28 regions
- current routing pool
- GPT-5.6 family
- Claude Opus 4.8
- OSS routing
- agentic model routing
- Global Standard
- Data Zone Standard
-
Azure AI Search:
- agentic retrieval
- Knowledge Agents
- Knowledge Sources
- retrievalInstructions
- outputConfiguration
- answerSynthesis
- strictPostFilter
- vector search
- hybrid search
- semantic ranking
- integrated vectorization
-
Foundry IQ:
- current positioning
- knowledge layer
- private agentic retrieval
- permission-aware knowledge
- integration with Azure AI Search / Foundry
-
Foundry Local:
- Azure Local
- vLLM
- multi-GPU
- tensor_parallel_size
- pipeline_parallel_size
- model evaluation
- automatic GPU inference tuning
- disconnected environments
- model caching
-
Azure Machine Learning:
- training
- endpoints
- MLflow
- pipelines
- registry
- compute
- AutoML
- current model deployment patterns
- current monitoring/evaluation features
-
Microsoft Agent Framework:
- current status
- relationship to Semantic Kernel
- relationship to AutoGen
- workflow/orchestration direction
- migration guidance
-
Retirements/deprecations:
- Azure OpenAI Assistants API
- classic Foundry Agent Service where applicable
- old hosted-agent backend
- Foundry Workflows if current retirement applies
- Prompt Flow lifecycle
- any retired Azure ML features
Never publish stale service status.
Build a logical Azure AI/ML hierarchy:
AZURE AI / MICROSOFT FOUNDRY │ ├── MICROSOFT FOUNDRY │ ├── Foundry Models │ ├── Foundry Agent Service │ ├── Foundry Tools │ ├── Foundry IQ │ ├── Model Router │ ├── Evaluations │ ├── Observability │ └── Foundry Local │ ├── AZURE OPENAI │ ├── Responses API │ ├── Realtime API │ ├── GPT models │ ├── embeddings │ ├── tool calling │ ├── multimodal │ ├── model deployments │ ├── provisioned throughput │ ├── global/data-zone deployments │ ├── quotas │ └── production troubleshooting │ ├── AGENTIC AI │ ├── Foundry Agent Service │ ├── Agent Runtime │ ├── Hosted Agents │ ├── Prompt Agents │ ├── MCP │ ├── A2A │ ├── Tools / Toolboxes │ ├── Identity │ ├── Memory │ ├── Tracing │ ├── Evaluation │ └── Multi-Agent │ ├── RAG / KNOWLEDGE │ ├── Azure AI Search │ ├── Foundry IQ │ ├── Knowledge Agents │ ├── Knowledge Sources │ ├── Vector Search │ ├── Hybrid Search │ ├── Semantic Ranker │ ├── Integrated Vectorization │ ├── Answer Synthesis │ └── RAG Troubleshooting │ ├── AZURE MACHINE LEARNING │ ├── Workspace │ ├── Studio │ ├── Training │ ├── Compute │ ├── Pipelines │ ├── MLflow │ ├── Registry │ ├── AutoML │ ├── Online Endpoints │ ├── Batch Endpoints │ ├── Model Deployment │ └── Production Troubleshooting │ ├── MLOPS / LLMOPS / GENAI OPS │ ├── DATA / ANALYTICS │ ├── AI INFRASTRUCTURE │ ├── SECURITY / GOVERNANCE │ ├── OBSERVABILITY │ ├── DEVOPS / IAC │ ├── INDUSTRIES │ ├── ROLE PAGES │ ├── INTERVIEW │ ├── JOB SUPPORT │ ├── PROFILE POSITIONING │ ├── CANDIDATE MARKETING │ ├── COUNTRY │ ├── CITY │ └── GUIDES / BLOGS / COMPARISONS
Create or enhance one authoritative parent hub.
Recommended target if missing:
/azure-ai-ml-job-support/
or equivalent existing primary Azure AI/ML hub.
Do not duplicate an existing hub.
The parent hub should naturally cover:
Microsoft Foundry Azure OpenAI Foundry Agent Service Azure Machine Learning Azure AI Search Foundry IQ RAG MLOps Foundry Tools Azure Databricks Azure AI infrastructure security observability production support interview support roles locations
Evaluate/create pages such as:
/microsoft-foundry-job-support/ /microsoft-foundry-production-support/ /microsoft-foundry-project-support/ /microsoft-foundry-models-job-support/ /microsoft-foundry-model-router-job-support/ /microsoft-foundry-model-evaluation-job-support/ /microsoft-foundry-observability-job-support/ /microsoft-foundry-troubleshooting-support/
Keep legacy synonyms in metadata/content where useful:
Azure AI Foundry Azure AI Studio
Do NOT create duplicate legacy pages unless separate migration intent exists.
Evaluate/create:
/azure-openai-job-support/ /azure-openai-production-support/ /azure-openai-responses-api-job-support/ /azure-openai-realtime-api-job-support/ /azure-openai-model-deployment-job-support/ /azure-openai-embeddings-job-support/ /azure-openai-tool-calling-job-support/ /azure-openai-multimodal-job-support/ /azure-openai-provisioned-throughput-job-support/ /azure-openai-global-deployment-job-support/ /azure-openai-data-zone-deployment-job-support/ /azure-openai-quota-throttling-support/ /azure-openai-cost-optimization-support/ /azure-openai-troubleshooting-support/
Only create if distinct intent exists.
Evaluate current model catalog and architecture.
Possible pages:
/microsoft-foundry-models-job-support/ /foundry-model-catalog-job-support/ /foundry-model-router-job-support/ /foundry-openai-models-job-support/ /foundry-claude-models-job-support/ /foundry-open-source-models-job-support/ /foundry-model-deployment-job-support/ /foundry-model-evaluation-job-support/ /foundry-model-routing-job-support/
Do not create a page for every model version.
Prefer family and use-case pages.
This is a high-priority 2026 topic.
Cover:
model routing routing pool GPT-5.6 Claude Opus 4.8 OSS models agentic routing cost quality latency Global Standard Data Zone Standard regional availability custom model subsets tool compatibility production routing
Possible pages:
/microsoft-foundry-model-router-job-support/ /foundry-model-router-production-support/ /foundry-model-router-cost-optimization/ /foundry-model-router-troubleshooting-support/
This should be one of the largest Azure GenAI clusters.
Evaluate/create:
/microsoft-foundry-agent-service-job-support/ /foundry-agent-service-production-support/ /foundry-agent-runtime-job-support/ /foundry-hosted-agents-job-support/ /foundry-prompt-agents-job-support/ /foundry-responses-api-agents-job-support/ /foundry-agent-tools-job-support/ /foundry-agent-toolbox-job-support/ /foundry-agent-memory-job-support/ /foundry-agent-web-search-job-support/ /foundry-agent-file-search-job-support/ /foundry-agent-code-interpreter-job-support/ /foundry-agent-mcp-job-support/ /foundry-agent-a2a-job-support/ /foundry-agent-authentication-job-support/ /foundry-agent-identity-job-support/ /foundry-agent-observability-job-support/ /foundry-agent-evaluation-job-support/ /foundry-agent-tracing-job-support/ /foundry-agent-troubleshooting-support/
High-value migration search intent:
/azure-openai-assistants-to-foundry-agent-migration/ /foundry-agent-classic-migration-support/ /foundry-hosted-agent-migration-support/ /autogen-to-microsoft-agent-framework-migration/ /semantic-kernel-agent-framework-migration/ /foundry-workflows-migration-guide/ /prompt-flow-migration-support/
Only create when current official retirement/migration guidance supports it.
Evaluate current August 2026 positioning.
Potential pages:
/microsoft-agent-framework-job-support/ /microsoft-agent-framework-multi-agent-support/ /microsoft-agent-framework-workflows-support/ /microsoft-agent-framework-azure-openai-support/ /microsoft-agent-framework-foundry-support/ /microsoft-agent-framework-mcp-support/ /microsoft-agent-framework-troubleshooting-support/
Also compare where useful:
Agent Framework vs Semantic Kernel Agent Framework vs AutoGen Agent Framework vs LangGraph Foundry Agent Service vs Agent Framework
Treat Foundry IQ as an important knowledge/RAG layer if current docs support it.
Possible pages:
/microsoft-foundry-iq-job-support/ /foundry-iq-agentic-retrieval-support/ /foundry-iq-private-knowledge-support/ /foundry-iq-enterprise-rag-support/ /foundry-iq-permission-aware-knowledge-support/
This is a major Azure RAG/search pillar.
Evaluate/create:
/azure-ai-search-job-support/ /azure-ai-search-vector-search-job-support/ /azure-ai-search-hybrid-search-job-support/ /azure-ai-search-semantic-ranker-job-support/ /azure-ai-search-integrated-vectorization-job-support/ /azure-ai-search-agentic-retrieval-job-support/ /azure-ai-search-knowledge-agents-job-support/ /azure-ai-search-knowledge-sources-job-support/ /azure-ai-search-answer-synthesis-job-support/ /azure-ai-search-strict-postfilter-job-support/ /azure-ai-search-indexer-job-support/ /azure-ai-search-rag-job-support/ /azure-ai-search-production-support/ /azure-ai-search-troubleshooting-support/
Create/connect Azure-specific RAG pages:
/azure-rag-job-support/ /azure-openai-rag-job-support/ /microsoft-foundry-rag-job-support/ /azure-ai-search-rag-job-support/ /foundry-agent-rag-job-support/ /foundry-iq-rag-job-support/ /azure-enterprise-rag-job-support/ /azure-rag-production-support/ /azure-rag-troubleshooting-support/
Include:
chunking embeddings vector indexing hybrid retrieval semantic ranking metadata filtering agentic retrieval Knowledge Agents Knowledge Sources answer synthesis citation grounding hallucination mitigation security cost latency
Evaluate current capabilities:
Azure AI Search vector Azure Cosmos DB vector search Azure Database for PostgreSQL + pgvector Azure SQL vector support if current Azure Managed Redis / Redis Cosmos DB agent state GraphRAG architectures where justified
Possible pages:
/azure-cosmos-db-vector-search-job-support/ /azure-postgresql-pgvector-job-support/ /azure-sql-vector-search-job-support/ /azure-managed-redis-ai-job-support/ /azure-cosmos-db-agent-state-job-support/
Create a complete Azure ML hierarchy.
Parent:
/azure-machine-learning-job-support/
Subpages:
/azure-ml-workspace-job-support/ /azure-ml-studio-job-support/ /azure-ml-training-job-support/ /azure-ml-compute-cluster-job-support/ /azure-ml-pipelines-job-support/ /azure-ml-mlflow-job-support/ /azure-ml-model-registry-job-support/ /azure-ml-automl-job-support/ /azure-ml-online-endpoint-job-support/ /azure-ml-batch-endpoint-job-support/ /azure-ml-model-deployment-job-support/ /azure-ml-inference-job-support/ /azure-ml-gpu-training-job-support/ /azure-ml-production-support/ /azure-ml-troubleshooting-support/
Build:
/azure-mlops-job-support/ /azure-mlops-pipelines-job-support/ /azure-mlops-mlflow-job-support/ /azure-mlops-model-registry-job-support/ /azure-mlops-ci-cd-job-support/ /azure-mlops-github-actions-job-support/ /azure-mlops-azure-devops-job-support/ /azure-mlops-model-promotion-job-support/ /azure-mlops-model-rollback-job-support/ /azure-mlops-retraining-job-support/ /azure-mlops-monitoring-job-support/
Evaluate/create:
/azure-llmops-job-support/ /azure-genai-ops-job-support/ /microsoft-foundry-genai-ops-support/ /azure-openai-llmops-support/ /azure-agent-ops-job-support/ /azure-ai-evaluation-job-support/ /azure-prompt-evaluation-job-support/
Current naming should use Foundry Tools while retaining legacy Azure AI Services search terms.
Create parent:
/microsoft-foundry-tools-job-support/
Possible children:
/azure-document-intelligence-job-support/ /azure-content-understanding-job-support/ /azure-ai-language-job-support/ /azure-ai-speech-job-support/ /azure-ai-vision-job-support/ /azure-ai-translator-job-support/ /azure-ai-content-safety-job-support/ /azure-speech-to-text-job-support/ /azure-text-to-speech-job-support/ /azure-ocr-document-processing-job-support/
Create distinct pages if justified:
/azure-document-ai-job-support/ /azure-document-intelligence-production-support/ /azure-content-understanding-job-support/ /azure-multimodal-ai-job-support/ /azure-document-rag-job-support/
Audit existing Databricks content before creating.
Potential Azure-specific pages:
/azure-databricks-ai-job-support/ /azure-databricks-mosaic-ai-job-support/ /azure-databricks-mlflow-job-support/ /azure-databricks-model-serving-job-support/ /azure-databricks-vector-search-job-support/ /azure-databricks-unity-catalog-ai-governance/ /azure-databricks-agentic-ai-job-support/
Connect Azure AI to:
Azure Data Lake Storage Gen2 Blob Storage Data Factory Synapse Microsoft Fabric Event Hubs Stream Analytics Cosmos DB Azure SQL PostgreSQL Databricks OneLake
Potential pages:
/azure-data-lake-ai-job-support/ /azure-blob-ai-job-support/ /azure-data-factory-ai-ml-job-support/ /azure-event-hubs-ai-job-support/ /microsoft-fabric-ai-job-support/ /azure-cosmos-db-ai-job-support/
Avoid creating generic data-engineering duplicates if existing pages own the intent.
Connect AI workloads to:
Azure Functions Azure App Service Container Apps AKS API Management Logic Apps Service Bus Event Grid Event Hubs Cosmos DB Key Vault Front Door
Potential pages:
/azure-functions-openai-job-support/ /azure-functions-foundry-job-support/ /azure-api-management-ai-job-support/ /azure-container-apps-ai-job-support/ /azure-logic-apps-ai-agent-job-support/ /azure-service-bus-ai-job-support/
Create where justified:
/aks-ai-ml-job-support/ /aks-generative-ai-job-support/ /aks-vllm-job-support/ /aks-gpu-ai-job-support/ /azure-container-apps-genai-job-support/ /azure-container-registry-ai-job-support/ /azure-kserve-job-support/ /azure-ray-ai-job-support/
High-priority 2026 emerging cluster.
Potential pages:
/microsoft-foundry-local-job-support/ /foundry-local-azure-local-job-support/ /foundry-local-vllm-job-support/ /foundry-local-multi-gpu-job-support/ /foundry-local-model-evaluation-support/ /foundry-local-disconnected-ai-support/ /foundry-local-gpu-tuning-support/
Cover:
vLLM multi-GPU tensor parallelism pipeline parallelism automatic GPU tuning model caching disconnected environments private AI sovereign AI
Create/connect pages for:
GPU VMs AKS GPU VM Scale Sets Azure Local Managed Lustre Blob / ADLS high-performance networking private AI container inference
Do NOT create every VM SKU as a separate page.
Create Azure AI security architecture:
/azure-ai-security-job-support/ /microsoft-foundry-security-job-support/ /azure-openai-security-job-support/ /azure-ai-private-endpoint-job-support/ /azure-ai-managed-identity-job-support/ /azure-ai-rbac-job-support/ /azure-ai-key-vault-job-support/ /azure-ai-private-link-job-support/ /azure-ai-vnet-job-support/ /azure-ai-governance-job-support/ /azure-ai-content-safety-job-support/
Include:
Entra ID Managed Identity RBAC Key Vault VNet Private Link Private Endpoint NSG Azure Policy Defender Purview audit data privacy
Create/connect:
/azure-ai-observability-job-support/ /microsoft-foundry-observability-job-support/ /foundry-agent-tracing-job-support/ /azure-openai-monitoring-job-support/ /azure-ml-monitoring-job-support/ /azure-ai-opentelemetry-job-support/ /azure-application-insights-ai-job-support/ /azure-ai-log-analytics-job-support/
Cover:
Azure Monitor Application Insights Log Analytics OpenTelemetry agent traces token usage latency endpoint failures request IDs distributed tracing evaluation datasets
Possible pages:
/azure-ai-cost-optimization-job-support/ /azure-openai-cost-optimization-support/ /azure-ml-cost-optimization-support/ /foundry-model-router-cost-optimization/ /azure-gpu-cost-optimization/ /azure-ai-finops-job-support/
Build:
/azure-ai-terraform-job-support/ /microsoft-foundry-terraform-job-support/ /azure-openai-terraform-job-support/ /azure-ml-terraform-job-support/ /azure-ai-bicep-job-support/ /azure-ai-github-actions-job-support/ /azure-ai-azure-devops-job-support/ /azure-genai-ci-cd-job-support/
Only where real intent exists:
/python-microsoft-foundry-job-support/ /python-azure-openai-job-support/ /python-azure-ml-job-support/ /dotnet-azure-openai-job-support/ /dotnet-microsoft-foundry-job-support/ /java-azure-openai-job-support/ /nodejs-azure-openai-job-support/ /typescript-microsoft-foundry-job-support/
Use current SDK names.
Evaluate:
Semantic Kernel Microsoft Agent Framework LangChain LangGraph AutoGen legacy/migration MCP A2A
Potential pages:
/semantic-kernel-foundry-job-support/ /langgraph-microsoft-foundry-job-support/ /langchain-azure-openai-job-support/ /mcp-microsoft-foundry-job-support/ /a2a-foundry-agent-job-support/
This cluster must be deep.
Create pages around real symptoms:
Azure OpenAI 429 quota exceeded throttling content filter deployment not found region/model availability Managed Identity auth Private Endpoint connectivity Responses API errors agent tool failure MCP connection failures A2A issues agent trace missing knowledge retrieval failures Search indexer failure vector dimension mismatch poor RAG retrieval semantic ranker issues Knowledge Agent errors Azure ML endpoint failure container health failure GPU OOM autoscaling MLflow tracking issues pipeline failures
Each troubleshooting page must follow:
SYMPTOM → POSSIBLE ROOT CAUSES → LOGS/METRICS → CONFIG/API CHECK → IAM/IDENTITY CHECK → NETWORK CHECK → FIX → VALIDATION → PREVENTION
Create/connect role pages:
Azure AI Engineer Microsoft Foundry Engineer Azure OpenAI Engineer Azure Generative AI Engineer Azure Agentic AI Engineer Foundry Agent Engineer Azure ML Engineer Azure MLOps Engineer Azure Data Scientist Azure AI Solutions Architect Azure AI Platform Engineer Azure RAG Engineer Azure LLM Engineer Azure AI DevOps Engineer Azure AI Security Engineer Azure AI Infrastructure Engineer Microsoft Agent Framework Engineer
Possible URLs:
/azure-ai-engineer-job-support/ /microsoft-foundry-engineer-job-support/ /azure-openai-engineer-job-support/ /azure-generative-ai-engineer-job-support/ /azure-agentic-ai-engineer-job-support/ /azure-ml-engineer-job-support/ /azure-mlops-engineer-job-support/ /azure-rag-engineer-job-support/ /azure-ai-solutions-architect-job-support/
Build interview-intent pages:
/azure-ai-ml-interview-support/ /azure-openai-interview-support/ /microsoft-foundry-interview-support/ /foundry-agent-service-interview-support/ /azure-rag-interview-support/ /azure-ai-search-interview-support/ /azure-ml-interview-support/ /azure-mlops-interview-support/ /azure-ai-engineer-interview-support/ /azure-ai-solutions-architect-interview-support/ /azure-agentic-ai-interview-support/ /microsoft-agent-framework-interview-support/
Also high-intent technical interview pages:
Azure OpenAI system design Foundry Agent system design Azure RAG system design Azure ML system design Azure MLOps system design AI Search architecture interview Agentic AI architecture interview
Use existing “proxy interview” terminology where the site already uses it for SEO.
However:
Do NOT claim impersonation or deceptive participation.
Describe support accurately as:
technical interview support mock interview architecture preparation technical mentoring coding practice scenario preparation expert guidance
Connect all technical pages to relevant job support pages.
Core:
Azure AI/ML Job Support Microsoft Foundry Job Support Azure OpenAI Job Support Foundry Agent Service Job Support Azure RAG Job Support Azure AI Search Job Support Azure ML Job Support Azure MLOps Job Support Azure Databricks AI Job Support Azure AI Production Support Azure AI Project Onboarding Support
Create only meaningful role-level pages:
/azure-ai-engineer-profile-positioning/ /azure-openai-engineer-profile-positioning/ /azure-ml-engineer-profile-positioning/ /azure-mlops-engineer-profile-positioning/ /azure-ai-solutions-architect-profile-positioning/
Potential:
/azure-ai-ml-candidate-marketing/ /azure-ai-engineer-candidate-marketing/ /azure-ml-engineer-candidate-marketing/ /azure-genai-engineer-candidate-marketing/
Connect to country funnels.
Build Azure AI/ML country architecture based on existing site markets.
Core countries:
USA Canada UK Ireland Germany Netherlands France Sweden Switzerland Australia New Zealand Singapore Hong Kong UAE Saudi Arabia Europe
Use existing naming conventions.
Potential pages:
/usa-azure-ai-ml-job-support/ /canada-azure-ai-ml-job-support/ /uk-azure-ai-ml-job-support/ /ireland-azure-ai-ml-job-support/ /germany-azure-ai-ml-job-support/ /netherlands-azure-ai-ml-job-support/ /france-azure-ai-ml-job-support/ /sweden-azure-ai-ml-job-support/ /switzerland-azure-ai-ml-job-support/ /australia-azure-ai-ml-job-support/ /new-zealand-azure-ai-ml-job-support/ /singapore-azure-ai-ml-job-support/ /hong-kong-azure-ai-ml-job-support/ /uae-azure-ai-ml-job-support/ /saudi-arabia-azure-ai-ml-job-support/ /europe-azure-ai-ml-job-support/
Do NOT clone the same text.
Country pages must include real differentiation:
- local Azure adoption
- relevant industries
- local Microsoft cloud regions where applicable
- common hiring roles
- timezone context
- remote/hybrid trends
- regulatory environment
- data residency
- financial/healthcare/public-sector patterns
- Foundry/Azure OpenAI availability where current
- local interview/job market terminology
Do not invent customers or offices.
Only for major search markets and distinct intent.
Tier 1 examples:
USA: Azure OpenAI Microsoft Foundry Azure ML Azure MLOps Azure AI interview
Canada: Azure OpenAI Azure AI/ML Azure ML Azure interview
UK: Azure OpenAI Microsoft Foundry Azure ML Azure AI interview
Germany: Azure AI Foundry Azure ML data residency/security
Australia: Azure AI Foundry Azure OpenAI Azure ML
Singapore: Azure AI Foundry Azure OpenAI
UAE: Azure AI Foundry Azure OpenAI
Do not mechanically generate every service × country.
Use the same city architecture already implemented on the site.
USA: New York San Francisco San Jose Seattle Boston Dallas Austin Chicago Atlanta Houston Los Angeles Washington DC Jersey City Charlotte Phoenix Tampa
Also evaluate existing supported city architecture before adding: Raleigh Denver Minneapolis Columbus Nashville Pittsburgh Salt Lake City
Canada: Toronto Vancouver Calgary Montreal Ottawa
Evaluate: Waterloo Mississauga Brampton Edmonton Halifax
UK: London Manchester Birmingham
Evaluate: Leeds Glasgow Edinburgh Bristol Cambridge Reading Nottingham
Ireland: Dublin Cork Galway Limerick
Germany: Berlin Munich Frankfurt Hamburg
Evaluate: Cologne Düsseldorf Stuttgart
Netherlands: Amsterdam Rotterdam Utrecht The Hague Eindhoven
France: Paris Lyon Toulouse Lille Marseille
Sweden: Stockholm Gothenburg Malmö
Switzerland: Zurich Geneva Basel Bern
Australia: Sydney Melbourne Brisbane Perth Adelaide Canberra
New Zealand: Auckland Wellington Christchurch
Gulf: Dubai Abu Dhabi Riyadh Jeddah
Do NOT create:
Microsoft Foundry × every city Azure OpenAI × every city Azure ML × every city AI Search × every city
unless actual search intent and sufficient differentiation exist.
Preferred architecture:
GLOBAL AZURE AI ↓ COUNTRY AZURE AI ↓ CITY AZURE AI/ML HUB ↓ AZURE OPENAI / FOUNDRY / AZURE ML / MLOPS / RAG ↓ JOB SUPPORT / INTERVIEW SUPPORT
Example:
Azure AI/ML → USA Azure AI/ML → New York Azure AI/ML → Azure OpenAI / Foundry / Azure ML → Job Support → Interview Support
City pages should include:
local industries technology hiring Azure ecosystem relevance financial services healthcare enterprise SaaS consulting cloud modernization AI/ML roles timezone remote/hybrid patterns interview patterns
Do not invent local offices or customers.
Connect Azure AI to:
Healthcare Financial Services Banking Insurance Pharma Retail Ecommerce Telecom Manufacturing Supply Chain Cybersecurity Government Enterprise
Possible URLs:
/healthcare-azure-ai-job-support/ /financial-services-azure-ai-job-support/ /banking-azure-ai-job-support/ /insurance-azure-ai-job-support/ /pharma-azure-ai-job-support/ /retail-azure-ai-job-support/ /government-azure-ai-job-support/
Cover where current:
Azure Health Data Services FHIR healthcare RAG Document Intelligence Content Understanding speech PHI HIPAA security private endpoints Azure OpenAI Foundry AI Search
Create only where search intent is unique.
Potential:
/what-is-microsoft-foundry-guide/ /microsoft-foundry-architecture-guide/ /foundry-agent-service-architecture-guide/ /azure-openai-production-architecture-guide/ /azure-ai-search-rag-guide/ /azure-ai-search-agentic-retrieval-guide/ /foundry-iq-guide/ /azure-machine-learning-architecture-guide/ /azure-mlops-guide/ /azure-rag-production-guide/ /azure-ai-security-guide/ /azure-ai-observability-guide/ /microsoft-agent-framework-guide/ /foundry-local-architecture-guide/
High-value comparisons:
Microsoft Foundry vs Azure Machine Learning Azure OpenAI vs Amazon Bedrock Microsoft Foundry vs Amazon Bedrock Foundry Agent Service vs Bedrock AgentCore Foundry Agent Service vs LangGraph Microsoft Agent Framework vs LangGraph Microsoft Agent Framework vs AutoGen Microsoft Agent Framework vs Semantic Kernel Azure AI Search vs OpenSearch Azure AI Search vs pgvector Foundry IQ vs custom RAG Knowledge Agents vs traditional RAG Azure OpenAI vs Foundry Models Azure ML vs SageMaker Azure ML vs Databricks ML Azure OpenAI vs self-hosted AKS Azure AI Search vector vs Cosmos DB vector RAG vs fine-tuning
Do not duplicate existing comparison pages.
After service hierarchy is complete, create a supporting blog cluster.
Prioritize:
Microsoft Foundry Production Architecture 2026 Foundry Agent Service Architecture Foundry Model Router 2026 Azure OpenAI Responses API Production Guide Azure AI Search Agentic Retrieval Guide Knowledge Agents + Knowledge Sources Foundry IQ Enterprise RAG Azure OpenAI RAG Troubleshooting Azure Machine Learning Production Architecture Azure MLOps with MLflow + Pipelines + Registry Azure ML Endpoint Troubleshooting Microsoft Agent Framework Architecture Foundry Local Multi-GPU vLLM Azure AI Interview Questions Azure OpenAI Interview Questions Microsoft Foundry Interview Questions Azure ML Interview Questions Azure MLOps Interview Questions
Blogs should funnel to service pages.
Every new page must have:
1 parent link 2–5 relevant sibling links 1 child/deeper link if applicable 1 commercial conversion link 1 inbound link from an existing relevant page
Every page must be reachable.
Required:
ORPHAN PAGE COUNT = 0
Add Azure AI/ML to the homepage Technologies area without cluttering the page.
Suggested visible group:
Microsoft Azure AI / ML
Link into the main hub.
Surface strong technologies:
Microsoft Foundry Azure OpenAI Foundry Agent Service Azure Machine Learning Azure AI Search Azure MLOps
Do not add 40 Azure links directly to homepage.
Update:
/technologies/
Create a clear Azure AI/ML group.
Example:
Azure AI & Microsoft Foundry
- Microsoft Foundry
- Azure OpenAI
- Foundry Agent Service
- Azure AI Search
- Foundry IQ
- Azure Machine Learning
- Azure MLOps
- Microsoft Agent Framework
- Foundry Tools
- Azure Databricks AI
- Foundry Local
Link to the parent hub and major child hubs.
Connect Azure AI to existing service intents:
Job Support Production Support Project Onboarding Interview Support Profile Positioning Candidate Marketing Get Interview Scheduled
Implement:
HOME → TECHNOLOGIES → AZURE AI/ML → MICROSOFT FOUNDRY → FOUNDRY MODELS / AGENTS / RAG → JOB SUPPORT / INTERVIEW
and:
HOME → SERVICES → JOB SUPPORT → AZURE AI/ML → AZURE OPENAI / AZURE ML / MLOPS
Add contextual links FROM relevant existing pages INTO the new Azure cluster.
Examples:
AI/ML parent pages cloud pages Azure pages .NET Azure pages RAG pages MLOps pages Agentic AI pages LLM pages vector DB pages DevOps pages data engineering pages
Do not force irrelevant links.
Use logical hierarchy.
Examples:
Home
Technologies Azure AI/ML Microsoft Foundry Foundry Agent Service MCP
Home
Technologies Azure AI/ML Azure Machine Learning MLOps MLflow
Home
Locations USA Azure AI/ML New York
Every page must have:
unique title unique meta description unique H1 canonical semantic H2/H3 Open Graph Twitter metadata breadcrumb schema page-appropriate JSON-LD FAQ only where useful internal links CTA accurate updated date
Do not keyword stuff.
Target natural variations:
Microsoft Foundry Job Support Azure AI Foundry Job Support Azure AI Job Support Azure AI ML Job Support Azure OpenAI Job Support Foundry Agent Service Job Support Azure AI Search Job Support Azure RAG Job Support Azure Machine Learning Job Support Azure ML Job Support Azure MLOps Job Support Microsoft Agent Framework Job Support Azure AI Production Support
Interview:
Microsoft Foundry Interview Support Azure OpenAI Interview Support Azure AI Interview Support Azure ML Interview Support Azure MLOps Interview Support Foundry Agent Interview Support Azure RAG Interview Support Azure AI Search Interview Support
Use “proxy interview” only where aligned with existing site terminology and search behavior.
Content must sound like it was written by engineers.
Use implementation terminology:
Foundry: resource project deployment model deployment Responses API conversation item response agent version tool call MCP A2A Toolbox Managed Identity RBAC trace OpenTelemetry
Azure OpenAI: deployment name model endpoint API version rate limits TPM RPM PTU content filters Responses API Realtime streaming embeddings global standard data zone
Azure AI Search: index indexer skillset vector field embedding knowledge agent knowledge source retrievalInstructions outputConfiguration answerSynthesis strictPostFilter semantic ranker hybrid query top-k filter
Azure ML: workspace job environment compute MLflow run model registry endpoint deployment batch endpoint autoscaling container artifact metrics
Infrastructure: VNet Private Endpoint Private Link Managed Identity Key Vault Entra ID RBAC NSG Azure Monitor Application Insights Log Analytics
Do NOT write generic AI marketing copy.
Never fabricate:
clients AWS/Azure partnerships Microsoft partnerships certifications ratings testimonials success rates company logos case studies customer names hiring data salary numbers regional availability
unless verified.
Every feature must be correctly identified as:
GA PREVIEW LEGACY RETIRED RETIRING
where that distinction matters.
Do not market preview features as fully GA.
Use current August 2026 information.
Do not automatically mark every old page as updated.
Only update dateModified when the page has actually been materially reviewed or changed.
Before creating ANY URL ask:
- Does it already exist?
- Does another URL already own the intent?
- Is the capability real and current?
- Is there enough technical depth for a page?
- Should it be a section instead?
- Will it cannibalize another page?
- Is there real search/commercial intent?
- Can it receive inbound internal links?
- Can it link naturally to a conversion page?
If any answer indicates thin/duplicate content:
SKIP PAGE.
Build an internal manifest with:
URL title category service subservice country city primary keyword secondary keywords search intent parent sibling group existing/new canonical schema CTA inbound links outbound links priority GA/preview/legacy status last technical verification date
Do not mass-generate before this manifest is complete.
P0:
Azure AI/ML hub Microsoft Foundry Azure OpenAI Foundry Models Foundry Agent Service Azure AI Search Foundry IQ Azure Machine Learning Azure MLOps Azure RAG Azure AI interview Azure OpenAI interview Azure ML interview major countries
P1:
Model Router Agent Service components Knowledge Agents Knowledge Sources Responses API Foundry Local Agent Framework MLflow Pipelines Model Registry AI Search subservices production troubleshooting major cities
P2:
Foundry Tools Databricks security observability data infrastructure frameworks industries IaC
P3:
comparisons long-tail migrations secondary cities special integrations
Do not create a giant:
SERVICE × COUNTRY × CITY
matrix.
Use:
GLOBAL AZURE AI → GLOBAL SERVICE → COUNTRY AZURE AI → CITY AZURE AI → COMMERCIAL SERVICES
Create specific service-country/city pages only if justified.
Inspect existing:
llms.txt llms-full.txt
Update using existing architecture to expose:
Azure AI hub Microsoft Foundry Azure OpenAI Foundry Agent Service Azure Machine Learning Azure AI Search MLOps RAG major guides major interview pages
Do not stuff thousands of URLs.
Ensure all valid pages enter the existing sitemap system.
Do not create competing sitemap logic.
Check:
canonical lastmod duplicate URLs orphan pages 404 redirect loops
Do not alter robots.txt unnecessarily.
Ensure the cluster is crawlable.
Use schema based on actual page type.
Potential:
WebPage Service TechArticle Article BreadcrumbList FAQPage where valid Organization only if already site-wide
Do not create fake Product ratings/reviews.
High-value pages should ideally be reachable within:
HOME → Technologies → Azure AI → service
or:
HOME → Services → Job Support → Azure AI
Keep P0 pages shallow.
After implementation run:
build lint tests route validation broken-link check duplicate slug check duplicate title check duplicate meta check duplicate H1 check canonical validation JSON-LD validation breadcrumb validation sitemap validation internal-link graph check orphan-page check mobile/responsive check
Fix all issues introduced.
Manually inspect representative pages from:
parent hub Foundry Azure OpenAI Agent Service AI Search Foundry IQ Azure ML MLOps security troubleshooting interview country city blog comparison
At completion provide:
- Latest August 2026 Microsoft sources reviewed
- Current names verified
- Retired/deprecated services identified
- Existing Azure URLs preserved
- Existing URLs enhanced
- New Azure AI hub pages
- Microsoft Foundry pages
- Foundry Models pages
- Model Router pages
- Foundry Agent Service pages
- Agent migration pages
- Microsoft Agent Framework pages
- Foundry IQ pages
- Azure AI Search pages
- Azure RAG pages
- Azure Machine Learning pages
- Azure MLOps / LLMOps pages
- Foundry Tools pages
- Azure Databricks pages
- Data pages
- AI infrastructure pages
- Security/governance pages
- Observability pages
- FinOps pages
- DevOps/IaC pages
- Role pages
- Interview pages
- Job-support pages
- Profile positioning pages
- Candidate marketing pages
- Country pages
- City pages grouped by country
- Industry pages
- Guides
- Blogs
- Comparisons
- Pages intentionally skipped
- Cannibalization avoided
- Homepage links added
- Technologies links added
- Services links added
- Reverse internal links added
- Sitemap updates
- llms.txt changes
- llms-full.txt changes
- Schema changes
- Build/lint/test results
- Broken-link count
- Orphan-page count
- Remaining recommended work
Required:
ORPHAN PAGE COUNT = 0
- Read this full instruction
- Audit repository
- Inventory existing Azure content
- Research Microsoft through August 2026
- Verify terminology
- Verify retirements
- Verify GA/preview
- Audit duplicate intent
- Build manifest
- Build parent hub
- Build Microsoft Foundry hub
- Build Azure OpenAI
- Build Foundry Models
- Build Model Router
- Build Foundry Agent Service
- Build Agent components
- Build migration pages
- Build Microsoft Agent Framework
- Build Foundry IQ
- Build Azure AI Search
- Build RAG
- Build vector/database integrations
- Build Azure Machine Learning
- Build Azure MLOps
- Build LLMOps/GenAIOps
- Build Foundry Tools
- Build document AI
- Build Azure Databricks AI
- Connect data services
- Build application integrations
- Build AKS/container AI
- Build Foundry Local
- Build infrastructure pages
- Build security
- Build observability
- Build FinOps
- Build DevOps/IaC
- Build language integrations
- Build frameworks
- Build troubleshooting
- Build roles
- Build interview cluster
- Build job-support funnel
- Build profile positioning
- Build candidate marketing
- Build country cluster
- Build city cluster
- Build industry cluster
- Build guides
- Build comparisons
- Build supporting blog content
- Update homepage
- Update Technologies
- Update Services
- Add reverse links from existing content
- Add breadcrumbs
- Add related content
- Add metadata
- Add structured data
- Update sitemap
- Update LLM discovery
- Build
- Lint
- Test
- Validate links
- Validate orphan count
- Fix all issues
- Produce final report
Build the complete Azure AI ecosystem on ProxyTechSupport.com around the CURRENT August 2026 Microsoft architecture.
The target graph is:
HOME → TECHNOLOGIES / SERVICES → AZURE AI / MICROSOFT FOUNDRY → MICROSOFT FOUNDRY / AZURE OPENAI / AGENT SERVICE / AZURE AI SEARCH / FOUNDRY IQ / AZURE ML / MLOPS → TECHNICAL SUBSERVICES → PRODUCTION / TROUBLESHOOTING / GUIDES / INTERVIEW → ROLE → COUNTRY → CITY → JOB SUPPORT / INTERVIEW SUPPORT / PROFILE POSITIONING / CANDIDATE MARKETING → WHATSAPP / CONTACT
The objective is:
MAXIMUM LEGITIMATE SEARCH COVERAGE + HIGH TECHNICAL AUTHORITY + ZERO THIN PROGRAMMATIC SPAM + ZERO ORPHAN PAGES + MINIMUM CANNIBALIZATION + CLEAR COMMERCIAL FUNNEL
DO NOT begin mass content generation until:
- repository audit is complete
- latest August 2026 Microsoft research is complete
- current service terminology is verified
- retirement/deprecation audit is complete
- existing URL inventory is complete
- cluster manifest is complete
- cannibalization audit is complete
After that, proceed directly through implementation and validation without asking for additional confirmation.