A product's data model—the core concepts and objects it prioritizes—determines whether new features create compounding advantages or just add to a feature list. Companies like Slack (persistent channels), Notion (blocks), Figma (shared canvas), and Rippling (employee records) succeeded by choosing non-obvious data models that became impossible for competitors to replicate without rebuilding from scratch. As AI commoditizes code execution, the data model becomes the primary moat. Horizontal tools innovate on how products are built, while vertical tools succeed by elevating the right domain objects. The key is identifying the atomic unit of work in your domain and ensuring every new feature strengthens that central concept.