Full AI Product Cycle

This article presents the 4D Method for building AI products: Discovery, Design, Development, and Deployment. The framework emphasizes that AI product development differs fundamentally from traditional software because problems can vanish as models advance, interfaces shape user trust expectations, and drift management requires continuous monitoring. The Discovery phase involves "truth hunting across shifting landscapes" using tools like the Discovery Debt Log and a 3-Lens test (durability, data, trust).

The Development and Deployment sections stress managing three types of drift—model, cost, and behavior—through golden datasets, monitoring, and escalation protocols. Rather than treating launch as an endpoint, teams must implement Day 2 infrastructure including dashboards, compliance automation, and rollback procedures. The article emphasizes building defensibility moats through distribution, trust, and rapid adaptation.