Ask an AI to write the product spec for a feature. If it feels wrong, re-prompt instead of editing. Then, have the AI generate a prompt for an image generator to create a visual mockup, allowing you to see the feature before committing to code.

Instead of creating multiple static mockups, prompt the AI to build a widget directly into a prototype that allows clicking through different design styles. This provides a live, interactive way to evaluate options within the actual user interface.

Instead of static mockups, prompt an AI to create a single HTML file containing multiple interactive UI options. This allows designers to quickly test and compare complex elements like animations or hover states, providing a faster and more tangible feedback loop for UI development.

The goal isn't to build one perfect prototype quickly. The real strategic advantage of AI tools is the ability to generate three or four distinct variations of a feature in a short time. This allows teams to explore a wider solution space and make better decisions after hands-on testing.

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.

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.

Stripe's internal AI prototyping tool, originally for designers, saw higher adoption from PMs. This initially caused nervousness but ultimately unblocked PMs, allowing them to explore ideas visually and improve cross-functional communication without waiting for design resources.

Instead of asking designers to create mockups from a verbal brief, PMs can use AI tools to generate multiple visual explorations themselves. This allows them to bring more concrete, refined ideas to the table, leading to a richer and more effective collaboration with the design team.

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.