rt-currier

What problem does it solve?

It helps you determine whether a business has real network effects, identify the specific type, and assess defensibility instead of guessing based on vague moat claims.

Core Features & Use Cases

• Network-effect diagnosis: Verifies whether a product truly has a network and whether value increases as more users participate.
• Taxonomy-based classification: Classifies network effects into the NFX framework (16 types across direct, 2-sided, asymptotic, data, and social) and identifies what drives strength.
• Defensibility assessment: Distinguishes network effects from the other main moats (embedding, scale, brand) and flags common “network effect” misconceptions.
• Failure mode checks: Tests for multi-tenanting, disintermediation, cherry-picking, and congestion that can erode the moat.

Quick Start

Ask the AI to diagnose your product’s moat by identifying the network nodes, the network topology, the applicable network-effect type from Currier’s taxonomy, and the likely strength drivers.