> Markdown version of [/videos/100449-headroom-a-context-optimization-layer-for-llm-applications?t=1071](https://www.wearedevelopers.com/videos/100449-headroom-a-context-optimization-layer-for-llm-applications?t=1071). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Headroom: A Context Optimization Layer for LLM Applications Are verbose JSONs exploding your LLM API costs? Headroom is an open-source optimization layer that safely shrinks context sizes by up to 90% without altering your codebase. - **Speakers:** [Devanshi Vyas](https://www.wearedevelopers.com/@devanshi-vyas) - **Event:** World Congress 2026 North America - **Published:** September 25, 2026 - **Duration:** 27:37 - **URL:** https://www.wearedevelopers.com/videos/100449-headroom-a-context-optimization-layer-for-llm-applications ## Access Playback and chapters for this video are available with a Free account. ## Related Moments - [Optimizing token costs and intelligent chunking strategies](https://www.wearedevelopers.com/videos/100168-event-driven-ai-agents-orchestrating-long-context-legal-processing-at-scale) (from "Event-Driven AI Agents: Orchestrating Long-Context Legal Processing at Scale") - [Using language models to compress prompt payloads programmatically](https://www.wearedevelopers.com/videos/1032-prompt-engineering-an-art-a-science-or-your-next-job-title) (from "Prompt Engineering - an Art, a Science, or your next Job Title?") - [Why most AI context remains unreachable for compression](https://www.wearedevelopers.com/videos/2148-why-token-reduction-isn-t-cost-reduction-dave-anderson-sarel-weinberger-phd) (from "Why Token Reduction Isn’t Cost Reduction - Dave Anderson & Sarel Weinberger, PhD.") - [Compressing the key-value cache using multi-head latent attention](https://www.wearedevelopers.com/videos/100477-understanding-llm-architectures-inside-the-design-of-modern-models) (from "Understanding LLM Architectures: Inside the Design of Modern Models") - [Optimizing AI token consumption and running local language models](https://www.wearedevelopers.com/videos/2135-wearedevelopers-live-streaming-html) (from "WeAreDevelopers LIVE - Streaming HTML") - [Optimizing AI infrastructure costs by maximizing token caching](https://www.wearedevelopers.com/videos/100024-what-500-production-environments-taught-us-about-shipping-ai-agents) (from "What 500+ Production Environments Taught Us About Shipping AI Agents") ## Related Articles - [6 Open-Source Tools to Reduce Your Token Usage](https://www.wearedevelopers.com/magazine/746-6-open-source-tools-to-reduce-your-token-usage) - [Introducing Redis Agent Memory Server](https://www.wearedevelopers.com/magazine/699-introducing-redis-agent-memory-server) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [A 5-Step Open-Source Setup for Agentic Engineering](https://www.wearedevelopers.com/magazine/738-a-5-step-open-source-setup-for-agentic-engineering) ## Related Jobs - [LLM Training Engineer](https://www.wearedevelopers.com/jobs/48420-llm-training-engineer) at **Sciforium** - [LLM Dataset Engineer](https://www.wearedevelopers.com/jobs/48419-llm-dataset-engineer) at **Sciforium** - [ML Engineer](https://www.wearedevelopers.com/jobs/48422-ml-engineer) at **Sciforium** - [Senior AI/ML Engineer](https://www.wearedevelopers.com/jobs/48352-senior-ai-ml-engineer) at **PagerDuty** - [ML Engineer](https://www.wearedevelopers.com/jobs/48448-ml-engineer) at **Docker, Inc.** - [Model Implementation Engineer](https://www.wearedevelopers.com/jobs/48421-model-implementation-engineer) at **Sciforium**