Get the Headroom Playbook

Your AI agent reads ten thousand tokens to answer one question — and you pay for every one. The fix everyone shows you (like caveman) trims what the model writes back. But the bigger leak is what it READS: every tool result, log, file, search hit and RAG chunk, stuffed into the context window and billed on every turn. This field guide is the free, open-source fix: Headroom (43,948+ GitHub stars, Apache 2.0), a compression layer that shrinks everything your agent reads BEFORE it reaches the model — 60–95% fewer tokens, the same answers, running 100% on your machine. Inside: why the input is the hidden half of your bill (with real workload numbers — 92% on code search, 92% on incident debugging, 73% on GitHub triage), how it works (the router + SmartCrusher/CodeCompressor/Kompress-base + CacheAligner), the reversible-compression trick (CCR — originals kept locally, retrieved on demand), the four ways to run it (wrap / proxy / library / MCP), the 60-second start, the public benchmarks proving accuracy holds (GSM8K ±0.0, TruthfulQA +3 points), and the output-shaper bonus that trims what the model writes too. Same answers, a fraction of the tokens.

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