Fine-tuned middleware reduces API costs for AI coding agents by 30% through token compression

A new open-source project introduces middleware to reduce costs for developers using AI coding agents like Codex. The solution is a local proxy that compresses the detailed outputs from tools like file retrieval and test runs before they are fed back into the AI model. This fine-tuned compression model cuts input token counts by 29.6% without disrupting the agent's reasoning process or internal cache. The development was driven by teams facing daily API costs of around $700 per person due to bloated context windows. The tool runs locally and is installed via a command-line shell script.