AI tools can spin up polished apps in a weekend, but speed makes it easier than ever to build the wrong thing. Here’s how to turn a “Lovable MVP” prototype into a real product that delivers value.

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AI tools like Lovable, Bubble, and Claude Code have compressed prototype timelines from weeks to days, but speed doesn't solve the core challenge of building the right product. Two real apps were built in a weekend each, illustrating both the power and the pitfalls of AI-generated software. The key risks: apps accumulate unnecessary features, drift into complexity, and reflect builder assumptions rather than user needs. The recommended approach is to prototype aggressively to learn fast, then apply disciplined product strategy before going to market — identifying the two or three biggest business risks early and designing the MVP to answer them. The fundamentals of product development (understanding users, testing assumptions, shipping the smallest valuable version) remain unchanged despite the tooling revolution.

How to launch a Lovable MVP in 2026

How to turn a Lovable prototype into a real product

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