The Problem You have a 400‑page internal handbook includes compliance rules, HR policies, engineering runbooks. You ask an LLM: “What’s the approval chain for a budget over $50k?” Without RAG, the model hallucinates: “The VP of Finance and the CTO must both approve.” But your real policy says: “Only the CFO for >$50k, plus a board note if >$200k.” The core problem: LLMs are frozen at training time . They don’t know your private documents. Fine‑tuning is expensive, lags behind updates, and still suffers from parametric knowledge bleed. RAG solves the specific problem of grounding generation in fresh, proprietary, or long‑tail facts without retraining . But naïve RAG (chunk → embed → retrieve → stuff into prompt) breaks in surprising ways. This article walks through one real failure, three common failure modes, and the guardrails we built to make RAG production‑ready.…