A curated list of AI tools and resources for developers, see the AI Resources .

Context Engineering

A practical handbook for designing, orchestrating, and optimizing context beyond prompt engineering.

Introduction

Context Engineering is a practical, first-principles handbook that moves beyond prompt engineering to the broader discipline of context design, orchestration, and optimization. It aggregates recent research and hands-on templates to help engineers and researchers build robust context systems combining retrieval, memory, tools, and orchestrated control flows.

Key Features

  • A layered framework from atomic prompts to field-theory inspired systems and protocol orchestration.
  • Course materials, runnable notebooks and templates to accelerate practical adoption and validation.
  • Community-driven repository that continuously integrates contemporary research and examples.

Use Cases

  • Education and training: structured curriculum for learning context engineering concepts and practices.
  • Production engineering: guidance for building systems with persistent memory, RAG, and multi-step orchestration.
  • Research: an indexed collection of papers, experiments, and reproducible examples for quick reference.

Technical Highlights

  • Emphasizes reproducible code-first examples and templates over slide-based descriptions.
  • Integrates RAG, memory architectures, and multi-agent orchestration patterns for long-horizon tasks.
  • Open-source under the MIT license, suitable for both academic and commercial reuse.

Comments

Context Engineering
Resource Info
🗺️ Guide 📖 Tutorial 🌱 Open Source