ai for product teams: from v0 to a feature that sticks
the path from a Lovable or v0 ai prototype to a production feature users adopt. what to build inside your own surfaces, with the support-ticket drop as proof.
ai for product teams. ai for product teams means shipping an ai feature inside your own product surfaces that users adopt and keep using. not a demo. a feature with a retention number and a support-ticket number behind it.
most product teams already have a prototype. you built it in a weekend with Lovable, Bolt, or v0. it looked great in the standup. then it stalled on the way to production.
the gap is not the model. the gap is everything around it. streaming, evals, audit logging, and a place in the product where the user already is. that is the work between a v0 screen and a feature your users keep.
why does the prototype stall before launch?
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