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With advanced AI coding tools and a robust design system, Snap's engineers build functional prototypes so quickly that the traditional design-first workflow is inverted. Instead of waiting for Figma mock-ups, teams now build and show working code to decide which ideas win.
The design process has shifted from comprehensive Figma mockups to live in-app prototypes built with AI coding assistants. Figma is now used sporadically to explore multiple variations of a specific component quickly, but it's no longer the start or end of the design journey.
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.
AI development tools have radically compressed the product design cycle. Instead of presenting wireframes or mockups, teams can now arrive at initial stakeholder meetings with fully functional, data-connected demos, dramatically accelerating the feedback loop and decision-making process.
Instead of creating static mockups in Figma, Cursor's design team prototypes directly in their AI code editor. This allows them to interact with the "life states of the app" and get a more realistic feel for the product, bridging the gap between design and engineering.
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.
High-fidelity, code-based prototypes are replacing static mockups as the primary artifact for design-to-engineering handoffs. At Stripe, engineers can use the prototype's code as a direct source of truth, minimizing translation errors and ambiguity from design to production.