Why AI Agent Demos Break in Production — And How to Build Systems That Last

AI agent demos often succeed while production deployments fail—a critical gap that separates marketing hype from real-world capability. This series teaches the engineering patterns behind building agents that work at scale: control loop design, state management across turns, tool integration via MCP, knowledge retrieval through RAG, and systematic skill composition. Understanding these foundational patterns—rather than relying on vendor tools—is essential for building AI systems that survive contact with production environments.