AI Product Strategy: Building Defensible Competitive Moats

Artificial intelligence is reshaping product development, but adopting AI tools without a strategic foundation often leads to generic features rather than sustainable value. This text-based course guides you through the strategic frameworks required to evaluate modern AI capabilities, identify authentic market differentiation, and build defensible product moats. You will explore how to transition from experimenting with surface-level AI tools to architecting product systems that compound value over time through proprietary data, specialized workflows, and clear user benefits. What you'll learn: - Understand foundational AI terminology, core architectures, and modern product capabilities - Evaluate AI opportunities using strategic frameworks to distinguish transient hype from lasting business value - Design data flywheels and feedback loops that strengthen your product's competitive moat - Analyze trade-offs between foundation model APIs, fine-tuning, and domain-specific integrations - Establish practical performance metrics, evaluation benchmarks, and ethical guardrails for AI features - Align cross-functional product, engineering, and business goals around realistic AI roadmaps The course begins with fundamental concepts and strategic frameworks before guiding you through structured case studies, design exercises, and actionable decision-making templates. It is designed for aspiring product managers, founders, and business leaders seeking a clear, accessible introduction to AI strategy without requiring technical or mathematical prerequisites. Start reading today to develop a clear, resilient AI roadmap for your products.