context-os-basics

A context operating system is a structured knowledge architecture that enables AI to compound intelligence over time. It uses a two-layer architecture combining atomic knowledge graphs with operational documents to maintain persistent, verifiable information.

Structure your knowledge graph taxonomy and ontology by defining system tags and hierarchical relationships using provided templates. This establishes the foundational two-layer architecture required for organizing atomic knowledge and operational documents.

Yes, building an information architecture for AI requires prerequisite knowledge of context operating systems and system architecture principles. This ensures you can properly implement the two-layer architecture and evidence-based attribution patterns.

Common anti-patterns in knowledge graph design for AI augmentation include lacking evidence-based attribution for claims and failing to separate atomic knowledge graphs from operational documents. The framework cautions against these structural pitfalls.

Ensure claims are backed by verifiable sources by applying evidence-based attribution patterns within your context operating system. This requires structuring your knowledge graph so every atomic claim links directly to its supporting evidence.