Most AI developers are building products backwards. They start with a foundation model, wrap it in an interface, and then wonder why users aren’t getting the results they need.
I see this pattern everywhere. Developers treat models like APIs: Plug them in, configure some parameters, and ship. But foundation models aren’t utilities — they’re starting points that engineers need to shape, train, and align with the specific problems their users face every day.
Why Generic Foundation Models Fail for Enterprise Applications
Consider a…

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