Research

Growth is no longer an advantage. It is a survival requirement. AI accelerates building, destabilizes channels, compresses tactic lifecycles, and raises customer expectations. Growth first, then defensibility.

Five misconceptions that kill AI companies. Speed is not a moat. Distribution is not a moat. Data alone is not a moat. Defensibility is a layered, time-sequenced process, not a destination.

AI compresses product development, but distribution, trust, adoption, and channel dynamics still obey growth fundamentals. Growth loops still rule. Bottlenecks move, they do not disappear.

AI breaks the SaaS pricing playbook. Usage-based pricing, outcome-based models, and value capture require better margin math for AI products.

Switching costs have collapsed. User loyalty is near zero. Most users arrive as AI tourists. Retention must be earned through disciplined activation, engagement, and resurrection design.

Working software is now a decision artifact. The advantage is not building more demos. It is reducing learning latency from hypothesis to customer signal faster than competitors.

How teams change when AI becomes part of the product. New roles, faster decisions, and the shift from shipping features to shaping model behavior.

Seven ways AI is changing customer expectations. Products are judged by AI-era standards: instant, contextual, proactive, even if they were not built for it.

Same role, new possibilities. How AI changes product management: from backlog grooming to capability design, from roadmap theater to faster learning.

Funnels stay linear. Loops compound. How to design acquisition systems where each user brings the next, with AI improving relevance each cycle.

A growth framework for the AI era. Product-market fit, product-channel fit, channel-model fit, and model-market fit are more fragile, faster-collapsing, and more critical than ever.

An evaluation-first approach to AI opportunities. Structured frameworks for sizing opportunities, judging risk, and deciding what to build or buy.