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Good read, but it stretches "data model" a bit. It's really about the product's conceptual/domain model, the primary entities you elevate and design around, and how that choice cascades into UX, pricing, and go-to-market. The examples (Slack channels, Notion blocks, Figma’s canvas, Toast's menu items) show how a strong model can compound value across features.

Where it blurs things: data model != UX strategy != business model, and success isn't only about a novel model, execution and distribution still matter greatly.

My takeaway: read "data model" here as "core conceptual model", and ask whether your product has a clear center that lets new features inherit context instead of becoming one-offs.



I would still defend the author that in fact once we look at a data model, we can see the limitations of the product. And there is no way to nullify all limitations; it will always be a tradeoff.




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