AI Prototyping Is Changing the Rules Between Designers and Developers

Every product team knows the pain: a designer brings polished static screens, the team gathers for a review, and it turns out half of the user scenarios were never thought through. What happens when loading fails? How does the interface behave with empty data? Where does this button lead? An exhausting ping-pong of comments and chat messages begins, and instead of handing the task to development, the team sinks into clarifications. Selectel's product group responsible for dedicated servers decided to break this vicious circle with AI prototyping tools, and its experience deserves attention.

The problem described by Selectel senior product manager Alya has been familiar to the industry for a long time. The classic waterfall approach to interface design, in which mockups are drawn first, then approved, then handed to developers, creates systematic time losses. Static pictures in Figma by definition cannot convey the dynamics of interaction. They show the ideal scenario but say nothing about edge cases, error states, transitions between screens, and responses to user actions. As a result, bugs in interface logic are discovered only after the code is written, and rework at that stage costs many times more.

AI tools are now actively moving into precisely this gap between static design and working code. Selectel's team turned to Figma Make, a relatively new service that uses generative artificial intelligence to turn mockups into interactive prototypes. Instead of manually specifying every interaction and every transition, the designer states an intent and the AI fills in the logic. This fundamentally changes iteration speed: what used to take days of painstaking prototyping now takes hours.

But it is not only about speed. The key advantage of AI prototypes is that they force the team to confront real usage scenarios much earlier in the development cycle. When the team looks at a working interactive mockup rather than a static picture, questions like "what happens if the data doesn't load" arise naturally, because the prototype literally demands an answer. Testers can check user scenarios before the first line of production code is written. Developers see a concrete model of interface behavior rather than abstract screens, which radically reduces the room for interpretation and misunderstanding.

Selectel's experience fits into a broader trend. Over the past year and a half, the market for tools at the intersection of design and development has boomed. Vercel released v0, an AI interface generator that works from a text description. Dozens of startups have appeared offering to turn screenshots and sketches into working code. Figma itself is actively integrating AI features into its platform. All these tools address the same fundamental problem: the gap between what the designer sees and what the developer understands. Artificial intelligence acts as a translator between two worlds, creating a shared artifact, a working prototype that both sides can evaluate unambiguously.

It is also important to stress the limits of the approach. AI prototypes replace neither designers nor developers. Generated code is rarely production-ready, and automatically built interaction logic may fail to account for the specifics of a given product. This is a tool for validating ideas, not a replacement for professional development. Judging by the description, Selectel's team uses these services exactly that way: as a means to quickly test a hypothesis and make sure all scenarios are covered before investing resources in a full implementation.

Still, the direction is set. The boundary between design and development will keep blurring, and AI tools will take on more and more of the routine work of turning visual ideas into working interfaces. For product teams still living in the cycle of endless approvals of static mockups, this is a signal to rethink their processes. Not because AI will magically solve all communication problems, but because it provides a tool that makes those problems visible at the earliest stage, when fixing them is still cheap.