My autonomous coding agent setup in Discord was running beautifully, but my monthly token bill was starting to look like a phone number. Every time my agent read a git diff, examined a database structure, or ran a deep directory search, it dumped thousands of lines of raw text into the conversation history. Since coding agents operate in multi-turn loops, reading this accumulated "context bloat" over and over quickly became incredibly slow and expensive.
That's when I found Headroom AI, an open-source tool designed to shrink agent prompt context by 60% to 95% using content-aware compressors (like Tree-sitter for code ASTs and SmartCrusher for JSON).
It sounded perfect. But when I tried to deploy it as a standard local proxy in my Docker Compose stack, I ran into a wall of TCP connection resets, 401 authentication errors, and broken tool calls.
This is the story of how I resolved those network bottlenecks, bypassed a frustrating GitHub Copilot gateway bug, and wrote a lightweight in-process TypeScript middleware to get Headroom running with 100% stability and massive cost savings.
The Initial Plan (And Why My Sockets Blew Up)
