Are you building AI systems that actually work in production - or just demos that impress in a sandbox? From Prompts to Agentic AI is a hands-on technical guide for engineers and architects who want to build production-grade AI systems on Azure. Written by an AI Architect with 11+ years of enterprise experience across Microsoft, WinWire, and global clients, this book takes you from foundational LLM concepts to fully deployed, observable, secure multi-agent systems. This is not a beginner's introduction to ChatGPT. This is a production engineering manual. WHAT YOU WILL BUILD: 10 complete, end-to-end Azure AI projects spanning enterprise sectors—HR policy automation, banking support agents, healthcare clinical RAG, legal document analysis, fraud detection, and executive decision intelligence. Every project includes full code, Azure deployment scripts, cost breakdowns, and architecture diagrams. WHAT YOU WILL LEARN: - Enterprise RAG architecture from first principles—chunking strategies, hybrid search, reranking, and retrieval optimization - Multi-agent orchestration using the orchestrator-specialist pattern with AutoGen, Semantic Kernel, and LangGraph - Agent memory systems: Short-Term Memory (Azure Redis), Long-Term Memory (Azure AI Search), and Episodic Memory (Azure Cosmos DB) - Learning & Adaptation Services with Human-in-the-Loop (HITL) feedback and RLHF - Production engineering: observability with Langfuse, evaluation with DeepEval, MLOps pipelines, and AKS deployment - Security and compliance: prompt injection defense, RBAC, Azure Key Vault, and GDPR/HIPAA patterns - Prompt engineering at scale: system prompt design, structured outputs, and chain-of-thought patterns WHO THIS BOOK IS FOR: Software engineers moving into AI engineering, AI developers building production systems, solutions architects designing enterprise AI platforms, and technical leads responsible for deploying LLM-based applications at scale. THE AZURE STACK: Azure OpenAI Service • Azure AI Search • Azure Cosmos DB • Azure Redis Cache • Azure Container Apps • Azure Kubernetes Service • Azure Key Vault • Azure Monitor • FastAPI • Semantic Kernel • AutoGen • LangChain • LangGraph • DeepEval • Langfuse By the end of this book, you will have the architecture knowledge, the code patterns, and the production engineering discipline to build AI systems that do not just work—they scale, they self-improve, and they earn trust in regulated enterprise environments.