We've had this conversation maybe a dozen times in the past year. A founder shows us a Lovable prototype, built over a weekend, looks great, users can click through it. Then they ask what it would take to actually ship it.
The prototype is fine. What's missing is everything underneath. No real database design. Auth that's half-baked. No error handling, no tests, a deployment story that's basically "it runs on my laptop." That's not a small gap. That's the whole product.
The prototype-to-production problem is real
Lovable, v0, Bolt, these tools are genuinely impressive for what they do. Get to a clickable demo fast, validate the concept, show stakeholders something real. That's the job they do well.
But they're not building production software. They're building demonstrations of production software. The difference matters enormously once real users show up, edge cases happen, and things break at 2am.
What TDD actually does in this context
Not lecture material here, practical reality from running this on client projects. When you write tests before the feature code, agents work better. Significantly better. The test is a specification. It tells the agent exactly what "done" means, which means the agent stops when it gets there instead of continuing to generate plausible-looking code that's slightly wrong.
We had a client last year, mid-sized SaaS, needed to take a Lovable MVP to production in six weeks. Without TDD the first attempt at agent-driven implementation kept drifting. Same spec, different results each run. Added test-first discipline: stabilised immediately. Agents need constraints to work well. Tests are constraints.
The infrastructure piece people underestimate
Cloud deployment isn't just "put it somewhere." For production you need: environments that match (dev, staging, prod, not "my laptop"), CI/CD that catches regressions before they reach users, monitoring that tells you something broke before your users do, and infrastructure that scales when traffic isn't what you planned.
None of that is in the Lovable export. All of it has to be built. That's most of what RSC does in these engagements. Not rewriting the prototype, adding the layer underneath it that makes it a real product.
What the actual path looks like
Architecture review first. What's salvageable, what needs rebuilding. Usually more is salvageable than you'd think, the UI logic is often fine, the data model needs work. Then test coverage before we touch anything. Then agent-driven implementation with humans reviewing every checkpoint. Then cloud deploy with CI/CD from day one, not bolted on later.
Six to ten weeks for a typical Lovable-to-production engagement, depending on complexity. Not fast, but faster than rebuilding from scratch. And you keep what you validated in the prototype phase. If you're at this stage, we're worth talking to.
🚀 RSC takes your AI prototype to production. Architecture, TDD, cloud deployment. The whole path. Talk to us.