Why most AI projects fail after the demo actually works

Building an AI demo is easy but running AI in production is hard and often fails.

Production AI systems must handle failures, control costs, integrate with infrastructure, and provide observability.

A reference production stack includes API layer, LLM orchestration, vector DB, tooling, guardrails, observability, and infrastructure.

The guide provides a sample implementation using FastAPI, LangChain, FAISS, and OpenAI models and stresses validation, state persistence, and separation of concerns.