Production reference for RAG (Retrieval-Augmented Generation) and AI agent development covering document parsing, chunking strategies (parent-child, contextual retrieval), embedding models, vector databases, hybrid search with reranking, GraphRAG, RAGAS evaluation, agent frameworks (LangGraph, CrewAI, Microsoft Agent Framework, Foundry Agent Service), MCP, multi-agent patterns, computer use, and Azure-native RAG (Azure AI Search, Foundry IQ). Use when designing or debugging RAG pipelines, choosing vector databases, building agent systems, evaluating retrieval quality, or architecting Azure AI Search solutions.
