The team dogfoods its product by taking screenshots of their live UI and using AI Studio to generate a functional clone. This allows them to rapidly prototype and iterate on new features for the very product they are building, achieving a working version in just over a minute.
Related Insights
Prototyping directly in the production environment makes high-quality interactions achievable without extensive resources. This dissolves the traditional design dilemma of sacrificing quality for speed, allowing teams to build better products faster.
AI coding agents enable "vibe coding," where non-engineers like designers can build functional prototypes without deep technical expertise. This accelerates iteration by allowing designers to translate ideas directly into interactive surfaces for testing.
The team no longer relies solely on PRDs and design docs. Product managers are now required to build a functional prototype as a core part of the development cycle, ensuring ideas are validated with a working model early on.
At OpenAI, the development cycle is accelerated by a practice called "vibe coding." Designers and PMs build functional prototypes directly with AI tools like Codex. This visual, interactive method is often faster and more effective for communicating ideas than writing traditional product specifications.
AI co-pilots have accelerated engineering velocity to the point where traditional design-led workflows are now the slowest part of product development. In response, some agile teams are flipping the process, having engineers build a functional prototype first and then creating formal Figma designs and UI polish later.
Historically, resource-intensive prototyping (requiring designers and tools like Figma) was reserved for major features. AI tools reduce prototype creation time to minutes, allowing PMs to de-risk even minor features with user testing and solution discovery, improving the entire product's success rate.
Instead of writing detailed specs, product teams at Google use AI Studio to build functional prototypes. They provide a screenshot of an existing UI and prompt the AI to clone it while adding new features, dramatically accelerating the product exploration and innovation cycle.
A practical AI workflow for product teams is to screenshot their current application and prompt an AI to clone it with modifications. This allows for rapid visualization of new features and UI changes, creating an efficient feedback loop for product development.
The V0 team dogfoods their own AI prototyping tool to define and communicate new features internally. Instead of writing specification documents, PMs build and share working prototypes. This provides immediate clarity and sparks more effective, tangible feedback from the entire team.
AI prototyping tools enable a new, rapid feedback loop. Instead of showing one prototype to ten customers over weeks, you can get feedback from the first, immediately iterate with AI, and show an improved version to the next customer, compressing learning cycles into hours.