Discovery & Reasoning Layer
Processes representations to reach decisions through AI-mediated reasoning, intent resolution, and selection.
Layer Principles
- •Intent Resolution: Translate needs to queries
- •Selection Readiness: Evaluate against constraints
- •Reasoning Transparency: Explain recommendations
- •Discovery Friction: Measure computational cost
- •AI-First Filtering: Pre-select relevant options
Primitives in this Layer
Discovery Friction
Discovery friction is the total cost AI systems incur to find and evaluate options in a market.
AI-Mediated Discovery
AI-mediated discovery is when AI systems find and filter options before presenting them to humans.
Intent Resolution
Intent resolution is the process of turning what humans want into what AI systems can search for.
Selection Readiness
An entity is selection-ready when AI systems can reliably evaluate it against specific requirements.
Related Layers
Encodes market-relevant information in machine-readable form optimized for AI reasoning rather than human browsing.
Analyzes value creation through machine understanding and the transition from attention to representation economics.
Provides frameworks and metrics for assessing representation quality, system performance, and economic outcomes.
Layer Architecture
The seven layers form an interconnected architecture. Primitives in this layer connect to Representation Layer, Economic Frameworks Layer and Measurement & Assessment Layer.