Leverage Figma's AI not for building entire prototypes, but to accelerate the design process. A PM can take an existing design, use Figma Make to generate variations for edge cases or error states, and then share those layered assets back with the designer, saving significant time.

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Vercel's Pranati Perry explains that tools like V0 occupy a new space between static design (Figma) and development. They enable designers and PMs to create interactive prototypes that better communicate intent, supplement PRDs, and explore dynamic states without requiring full engineering resources.

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.

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.

To break out of a linear design path, use AI tools that can generate multiple, distinct design options from a single prompt or command. For example, Magic Patterns’ '/inspiration' command produces four variants, allowing for rapid brainstorming and side-by-side comparison of different approaches.

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.

AI prototyping should be viewed as a fundamental skill for modern PMs, not an extra job responsibility. Just like using Figma to communicate design, AI prototyping tools allow PMs to make abstract AI concepts tangible for stakeholders and customers. This accelerates feedback loops and improves alignment on complex product behaviors.

AI often generates several good ideas across multiple prototypes. Instead of recreating them manually, use a tool like Subframe that allows you to directly drag and drop components from one AI-generated variant into another. This 'kitbashing' approach accelerates the creation of a polished design.

When exploring UI solutions, use a tool like Magic Patterns and its "Inspiration Mode" to generate multiple, distinct design approaches from a single prompt. By asking the AI to "think expansively and make each option differentiated," product managers can quickly explore a wide solution space and avoid getting stuck on a single initial idea.

In an AI-driven workflow, the primary value of a rapid prototype is not for design exploration but as a communication tool. It makes the product vision tangible for stakeholders in reviews, increasing credibility and buy-in far more effectively than a slide deck.