AI Product Strategy 101

This article presents a comprehensive framework for AI product strategy, arguing that success requires building defensible moats rather than simply adding AI features. The piece outlines three key lenses: identifying where to compete (Pioneer, Disruptor, or Enhancer), determining how to win through proprietary data and transformed workflows, and executing effectively while managing AI-specific challenges like cost-capability trade-offs and silent failures.

The content provides practical guidance through seven implementation steps and a detailed checklist, emphasizing that "models are a commodity" while "data moats" provide lasting competitive advantage. The author warns against three critical pitfalls: fighting giants head-on, relying on superficial demos, and building shallow wrappers on third-party APIs without proprietary differentiation.