Come and explore with me
Model Context Protocol Part 5: Integrating MCP Servers with Azure AI Foundry and Claude
Advanced Prompt Engineering Patterns for Claude in Azure AI Foundry
Model Context Protocol Part 4: Enterprise Integration Patterns – Security, Scaling, and Production Deployment
Model Context Protocol Part 3: Building MCP Servers in Node.js and C# – Cross-Platform Implementation Guide
Model Context Protocol Part 2: Building Your First MCP Server with Python and FastMCP
Model Context Protocol Part 1: Understanding the New Standard for AI-Data Integration
Vector Databases Part 8: Lessons Learned and Reality Check
How to Setup Docker: Complete Installation Guide for Linux, Windows, and macOS
Vector Databases Part 7: Production Deployment Patterns and Operations 
A comprehensive developer guide to CasperCG, the professional broadcast graphics system used by TV stations and media companies worldwide. Learn architecture, AMCP commands, template development, and real-world integration examples.
Learn how Azure Web App Service deployment slots enable zero-downtime deployments, safe testing environments, and instant rollbacks. This comprehensive guide covers everything from basic concepts to advanced implementation strategies.
Complete your AI foundation with production-ready smart memory management that controls costs while maintaining conversation context.
Solve the AI amnesia problem by adding LangChain conversation memory, enabling your assistant to remember context across multiple messages.
Transform your basic Node.js app into an AI-powered application by integrating Azure OpenAI Service for intelligent responses.
Create the foundation project structure for our AI customer support assistant application.
Begin your journey into AI application development by understanding why Node.js, LangChain, and Azure OpenAI Service create the perfect foundation for building intelligent, conversational applications.
Part 8 completes our comprehensive series by exploring deployment pipelines and DevOps practices that enable safe, frequent releases to systems serving millions of users. We dive deep into Azure DevOps, advanced deployment strategies, feature flags, and building delivery systems that transform deployment from a risky event into a routine operation.
Part 7 explores building comprehensive observability that transforms complex systems from black boxes into transparent, self-diagnosing platforms. We dive deep into Azure Monitor, intelligent alerting systems, distributed tracing, and operational excellence practices that enable proactive system management at scale.
Part 6 explores the critical balance between system performance and operational costs. We dive deep into intelligent cost optimization, performance engineering at scale, and building systems that automatically optimize for both speed and efficiency while serving millions of users.
