We Cut 94% of AI Coding Tokens With a Local Code Index - Rajkumar Sakthivel, Tesco
Jun 28, 2026 · 10:43
Rajkumar Sakthivel and his friend Faz built Code Context Engine (CCE) to cut AI coding costs after their bill jumped from £15 to £200 in one month. They found that 45,000 tokens were sent per query but only 5,000 were needed, with 90% of cost being input context. Their solution is a local retrieval layer that uses AST-aware chunks, combined vector and keyword search, and a weighted scoring heuristic (50% meaning, 30% keyword, 20% recency) that runs in 0.4 milliseconds. On a FastAPI test, tokens per question dropped from 83k to 4.9k—a 94% reduction—with 90% accuracy. They emphasize that fixing the input, not the model, yields the biggest savings, and their open-source tool shares a single index across Claude Code, Cursor, Copilot, and Codex.
