Slashing LLM Context by 97%: A Revolutionary Approach Without Embeddings

This brilliant approach showcases a massive leap in Prompt Engineering and LLM efficiency by drastically reducing the Context Window from 80K to just 2K tokens. The lightweight indexing system leverages structural signals and simple heuristics to deliver highly relevant codebase context without relying on vector databases or Retrieval-Augmented Generation (RAG). It is incredibly inspiring to see that structured context can often matter far more than simply increasing model size or Parameter counts.