This repository provides a comprehensive, first-principles handbook for "Context Engineering," a discipline focused on optimizing the entire information payload provided to Large Language Models (LLMs) beyond simple prompt engineering. It targets researchers, developers, and power users seeking to build more sophisticated and capable AI systems by systematically designing, orchestrating, and refining the context window.

How It Works

The project frames context engineering through a biological metaphor, progressing from "atoms" (single instructions) to "neural fields" and "protocol systems." It emphasizes a structured, iterative approach, incorporating concepts like few-shot learning, memory systems, retrieval augmentation, control flow, and cognitive tools. The core idea is to treat the context window not as a static input, but as a dynamic, evolving "field" that can be manipulated and optimized for emergent reasoning and symbolic manipulation.

Quick Start & Requirements

• Install/Run: Explore Jupyter notebooks (.ipynb files) within the 10_guides_zero_to_hero/ directory.
• Prerequisites: Python environment.
• Resources: Minimal computational resources for initial exploration; more significant resources for running complex examples.
• Links: README, DeepGraph, NotebookLM Chat.

Highlighted Details

• Research-Backed: Integrates findings from over 1400 research papers, citing work on memory and reasoning (MEM1), cognitive tools (IBM Zurich), and emergent symbolic mechanisms (ICML Princeton).
• Structured Learning Path: Offers a clear progression from foundational theory to practical implementation and advanced concepts.
• Code-First Approach: Provides runnable code examples, templates, and schemas for direct application.
• Inspired by Leaders: Adopts a style and methodology influenced by Andrej Karpathy and 3Blue1Brown.

Maintenance & Community

• Community: Active Discord server available via badge link.
• Links: Discord, DeepWiki.

Licensing & Compatibility

• License: MIT License.
• Compatibility: Permissive license suitable for commercial and closed-source use.

Limitations & Caveats

The project is explicitly marked as "Under Construction," indicating that many components, guides, and examples are still being developed. The depth and breadth of the material suggest a significant learning curve for users aiming to master the advanced concepts like neural field theory and symbolic mechanisms.