Contrary to traditional digital design, the modern AI-assisted workflow involves broad, conceptual exploration on canvas-like tools (e.g., Paper) and sweating the final visual details directly in code. Pixel-nudging in design software like Figma is becoming obsolete for last-mile fit and finish.

AI-powered "vibe coding" is reversing the design workflow. Instead of starting in Figma, designers now build functional prototypes directly with code-generating tools. Figma has shifted from being the first step (exploration) to the last step (fine-tuning the final 20% of pixel-perfect details).

Historically, design workflows moved from low-to-high fidelity due to tool constraints. AI tools like Codex remove these barriers, allowing designers to begin with functional wireframes in code for immediate interaction testing, bypassing static sketches.

AI makes iterating in code as inexpensive as sketching in design tools. This allows teams to skip low-fidelity wireframes and start with functional prototypes, blowing up traditional, linear development processes and reinventing workflows daily.

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.

Instead of designing in Figma first, Ron Goldin used AI to generate a functional but ugly "build wireframe" for his product. This approach allows for rapid iteration on core flows and architecture, ensuring the product feels right before investing in high-fidelity design.

A prototype-first culture, accelerated by AI tools, allows teams to surface and resolve design and workflow conflicts early. At Webflow, designers were asked to 'harmonize' their separate prototypes, preventing a costly integration problem that would have been much harder to fix later in the development cycle.

Instead of coding prototypes, OpenAI PMs use AI image generation to rapidly create multiple design mockups from a single screenshot and a text prompt. This offers a much faster iteration loop for exploring UI ideas before any code is written.

Building a true AI product starts by defining its core capabilities in an AI playground to understand what's possible. This exploration informs the AI architecture and user interface, a reverse process from traditional software where UI design often comes first.