Building Your Own "Google Maps for Codebases": A Guide to Semantic Code Search with LLMs

From Keyword Chaos to Semantic Understanding You’re staring at a massive, unfamiliar codebase. A senior engineer says, "The logic for processing user subscriptions is in here somewhere." You grep for "subscription," but get 500 results across controllers, models, services, and tests. You try "billing," "renewal," "payment"—each a new avalanche. Hours later, you’re deep in a rabbit hole, no closer to the answer. This is the problem of keyword search . It matches strings, not meaning. What if you could instead ask, "Where's the code that handles a failed credit card charge during a monthly renewal?" and get a direct link to the relevant file and function? This "Google Maps for Codebases" concept, highlighted by a recent popular article, isn't magic—it's semantic code search powered by Large Language Models (LLMs) . In this guide, we'll move from concept to implementation. We'll build a minimal, functional system that lets you ask questions in plain English and find the corresponding code