Glossary
Key terms and concepts in context engineering and AI agent productivity.
AI Power Equation
A framework expressing AI effectiveness as the product of four factors: Capability, Alignment, Duration, and Throughput. Improving any factor multiplies total output.
Codebase Cartography
The methodology of systematically mapping a codebase's architecture, intent, and tribal knowledge into structured context that AI agents can navigate.
Context Engineering
The practice of structuring and delivering the right context to AI agents so they can reason effectively about complex systems.
Intent Layer
A hierarchical context system that lives inside your repository, giving AI agents a structured map of your codebase's architecture, patterns, and decisions.
Intent Nodes
Small, structured files (like AGENTS.md) placed in key directories that declare the purpose, patterns, and boundaries of that area of the codebase.
Progressive Disclosure
A context-loading strategy where AI agents start with high-level system context and progressively drill into detailed context only for the areas relevant to their current task.