Building an AI demo takes a weekend. Building a production AI system takes months. The demo works perfectly when you show it to your manager, carefully chosen inputs, ideal conditions, no edge cases. Then you deploy it to real users. Someone pastes in a 50,000-word document. Another user asks questions in a language you didn't test. Your API bill triples on a Monday morning because of a viral tweet. The model starts hallucinating about a topic your training data didn't cover. Production AI engineering is the discipline of anticipating everything that can go wrong and building systems that handle it gracefully, evaluation, safety guardrails, monitoring, cost controls, and graceful degradation all working together.