AI-generated prototypes can move fast, but production users need architecture, security, tests, observability, and maintainable code. The right move is not always to throw the prototype away; it is to identify which parts are useful and which parts are fragile.

A productization sprint audits the code, rebuilds risky paths, adds reliable deployment, and creates a roadmap from demo to durable product.