AI can build an MVP quickly when the scope is narrow, the requirements are clear, and the product uses common patterns. It is especially useful for prototypes, dashboards, simple SaaS flows, internal tools, and first versions that need validation before heavy engineering investment.
The speed comes from automating repetitive implementation work: setting up screens, routes, basic data models, authentication flows, tests, and integrations. The risk is overbuilding or accepting fragile code because the demo looks finished.
Verdent's angle is MVP execution with planning and review. A user can describe the product goal, use Plan Mode to turn it into steps, let agents implement scoped tasks, and review changes before moving forward. The best MVP workflow is not "AI builds everything instantly." It is "AI helps build the smallest testable version quickly and safely enough to learn from users."
