A Netflix senior engineer just open-sourced the tool you wish you’d written. Headroom (LLM context compression) jumped 1,000+ GitHub stars in a single day, and the pitch is brutally simple: most of the tokens you’re paying for are junk.
What it actually does
Headroom sits as a transparent proxy between your app and any of 100+ models (OpenAI, Anthropic, Google via LiteLLM). Before tool outputs, logs, RAG chunks, files, or chat history hit the model, it compresses them — 60–95% fewer tokens, same answers. The trick is it’s reversible: it stores the original and hands the LLM a retrieval tool to pull back full content on demand. So you compress aggressively without losing anything. An AST compressor handles code, JSON/DOM compressors kill boilerplate, and “squashers” trim the rest statistically.
Why it’s worth watching
Token cost is the silent killer of agent economics — Tejas Chopra reckons up to 90% of what you send is redundant. Headroom ships as a library, a proxy, or an MCP server, so you bolt it on without rewriting anything. Creator claims ~$700K saved and ~200B tokens reclaimed already. For anyone running agents at scale, that’s not a nice-to-have.
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