In an era where speed and creativity go hand in hand, I am using ChatGPT and Magic Patterns to “vibeframe,” leveraging AI to wireframe complex, multi-screen designs.

Lately I have been working on projects that are large, greenfield, and zero-to-one in scope. These are the kinds of projects where grab-and-go components or Mobbin screen rips are not always available. In those moments, wireframes are still a useful way to sketch a planned experience and build early alignment with teammates. While wireframing can quickly become involved, I try to keep it fast and high level, focusing on resolving functional questions without inviting premature hi-fi feedback. I also find the current generation of design tools more compelling for wireframing than for polished UI work. It is easy for them to slip into uncanny valley territory, looking almost right but feeling subtly off. Staying low-fi plays to their strengths, keeps the team focused on layout, flow, and core interactions, and most importantly makes us incredibly fast in the early ideation phase.

To move faster without losing design intent, I have started embracing what I call Vibeframing. This is my way of using generative AI early in the design process to capture both the structure and the vibe of a product. In 2025, the biggest edge in design is the ability to move quickly, and tools like Magic Patterns make it possible to generate interactive wireframes and iterate on ideas at a pace that was not realistic before. By letting AI handle the rough first drafts, I can spend more time on nuance, judgment, and UX decisions.

My vibeframing workflow begins with a solid foundation, usually an outline or PRD. I feed that into ChatGPT and ask it to think like a lead product designer, with the goal of surfacing unanswered questions, gaps, or edge cases that might trip us up later. Once those issues are identified, I collaborate with Product Management to clarify and update the PRD. From there, I ask ChatGPT to translate the refined requirements into a concise prompt for Magic Patterns. In practice, this means using AI to talk to AI. ChatGPT distills the design intent into clear instructions that Magic Patterns can act on. While I have tried dropping a full PRD directly into Magic Patterns, I consistently get better results when I first distill it into something that emphasizes the design problem and structure.

With a tailored prompt in hand, I jump into Magic Patterns and generate wireframes for the various screens and interactions. I often ask it to produce multiple versions of key screens and toggle between them to explore different directions. Seeing a complex experience materialize almost instantly is still a little surprising, especially when it lands close to the mark.

[Screenshot: Magic Patterns generating multiple wireframe variations for a complex user flow in grayscale.]

Once the wireframes capture the intended user journey, I move into high-fidelity design. Magic Patterns can export to Figma, but I usually just bring in a screenshot or link as a reference. From there, I use our component library to translate the low-fi structure into a polished interface. By this point, most of the heavy lifting has already been done. The hi-fi phase becomes about refinement rather than invention. While we may still wireframe in Figma occasionally, more and more of the early exploration now happens in Magic Patterns, with Figma reserved for final execution.

[Screenshot: Magic Patterns wireframe brought into Figma and rebuilt with the design system]

Vibeframing has been a meaningful shift in how I work. The upfront effort of refining the PRD and crafting a strong prompt consistently pays off, since the initial outputs from Magic Patterns are often surprisingly close on the first pass. By the time I open Figma, there is very little guesswork left. None of this replaces the creativity or judgment of a human designer. If anything, it amplifies it. I spend less time pushing pixels on empty artboards and more time thinking, shaping, and telling the right product story. Vibeframing sits right at that intersection, blending human intent with AI speed to help designs land faster without losing their soul.