How I reduced AI codebase context from 100K to 5K tokens using a graph-based RAG

Most AI coding tools lie to you about context. They say "I understand your codebase." What they actually do is dump as many files as possible into the context window and hope the model figures it out. That works on a 3-file project. It falls apart on anything real. Here's the problem I kept hitting: a medium-sized production codebase hits ~100K tokens when you try to feed it to an LLM. That's expensive, slow, and surprisingly lossy — models start hallucinating relationships between files that do