AI has democratized world‑class search — what once cost millions to build is now within reach. This talk shares how Platzi moved from Algolia to an edge‑first semantic search engine, evolving from basic keyword matching to understanding intent across languages, personalizing results per student, and uncovering content relationships we didn’t know existed. We show how we unify search, instant search, and recommendations into a single relevance layer with real‑time, user‑aware re‑ranking, delivering global performance without sacrificing latency. We discuss the production architecture and practices that made it robust and share how we validate changes before release — staged rollouts behind feature flags with canaries and A/B tests — so updates are safe before full deployment.