adminAI Social Retention: How Investors Should Read D1, D7 and D30 Behavior
An investor framework for reading AI social retention through activation, cohort behavior, relationship depth and inference economics.
AI Social Safety as Infrastructure: Why Moderation Becomes a Business Moat
Why safety, identity governance, age controls and moderation can become core infrastructure—and a business moat—for AI social platforms.
Creator AI Supply: How Platforms Build a Defensible Marketplace of Personalities
A business framework for creator AI supply: acquisition, onboarding, rights, quality, activation and marketplace defensibility.
AI Personality Marketplace Economics: Discovery, Conversion and Creator Payouts
How AI personality marketplaces work economically across discovery, fan conversion, creator payouts, generation costs and retention.
AI Social Platform KPIs: A Board-Level Dashboard for Growth and Quality
A board-level KPI framework for AI social platforms covering activation, retention, payer conversion, creator supply, inference cost and safety.
AI Social Due Diligence: 12 Questions Investors Should Ask Founders
Twelve due-diligence questions for AI social startups covering retention, inference economics, identity rights, creator supply, safety, distribution and defensibility.
AI Companion Market Segmentation: Five User Jobs Behind One Fast-Growing Category
The AI companion market contains distinct jobs: everyday conversation, entertainment, creator access, roleplay and personal development. Each implies different economics.
Creator AI Distribution: Why Audience Ownership Matters More Than Model Choice
Creator AI businesses compete on distribution as much as technology. Audience ownership, attribution, onboarding and cross-platform funnels shape durable economics.
AI Identity Infrastructure: Why Persistent Personas Need More Than a Foundation Model
Persistent AI personas require identity infrastructure for memory, policy, multimodal consistency, permissions and versioning beyond the foundation model.
AI Social Unit Economics: The Metrics Investors Should Model Before Growth
A practical framework for AI social unit economics across acquisition, payer conversion, retention, inference cost, creator share and contribution margin.
