# context engineering

Context compression for LLM apps and coding agents

Headroom is an Apache-2.0 context compression layer for LLM apps and coding agents. It compresses tool output, logs, files, RAG chunks, and agent history through a local library, proxy, wrapper, or MCP server, with retrieval hooks for bringing originals back when needed. Treat its savings numbers as Headroom-reported benchmarks, not independent aicoolies measurements.

Context engineering platform for AI agents with temporal knowledge graphs

Zep is a context engineering platform that assembles relationship-aware context for AI agents from conversations, business data, documents, and events. It maintains a temporal knowledge graph that automatically extracts entities and relationships, tracking how context evolves over time. Zep delivers formatted context blocks optimized for LLMs with sub-200ms latency, integrating with LangChain, LlamaIndex, AutoGen, and Google ADK through Python, TypeScript, and Go SDKs.

Context engineering patterns for AI coding assistants

Context Engineering Intro is an open-source repository by Cole Medin providing structured context engineering patterns for AI coding assistants. Built around Claude Code, it includes .claude command files, PRP templates, and the WISC framework for managing AI context in coding sessions. The repo shows how to structure project context and rules so AI assistants produce reliable, architecture-aware code. With 13K+ GitHub stars, it is a go-to reference for context-first AI coding.