Context Engineering
Overview
Context engineering is the evolution beyond simple prompt engineering. It's "the delicate art and science of filling the context window with just the right information for the next step" as defined by Andrej Karpathy.
Unlike prompt engineering which focuses on "what you say", context engineering encompasses "everything else the model sees" - including examples, memory, retrieval, tools, state, and control flow.
Key Concepts
From Theory to Practice
- Information Management: Providing the right information, tools, and format for LLMs
- System Architecture: Dynamic context assembly from multiple sources
- Context Optimization: Token budget management, KV-cache optimization, and context pruning
Core Principle
Context engineering allows us to ship improvements in hours instead of weeks, keeping our product orthogonal to the underlying models: If model progress is the rising tide, we want to be the boat, not the pillar stuck to the seabed.
— Manus Team
Navigation
📚 Learn More
- What is Context Engineering? - Complete guide with definitions, patterns, and best practices
- Manus Context Engineering - Real-world implementation insights
🔧 Implementation Patterns
The complete guide covers essential patterns including:
- KV-Cache Optimization - Stable prefix templates for better performance
- Tool Masking - Smart tool availability management
- File System as Context - Using persistent storage for extended context
- Attention Manipulation - Todo list recitation and focus management
- Error Preservation - Learning from failures in context
- Multi-Agent Orchestration - Context engineering for agent systems
🎯 Best Practices
- Design around KV-cache for production systems
- Structure information architecture clearly
- Implement proper tool and memory management
- Preserve errors for learning opportunities
- Optimize attention and focus management
Ready to dive deeper? Start with What is Context Engineering? for comprehensive patterns and implementation details.