The rise of GenAI tools is reshaping how designers create interfaces. Instead of manually adjusting elements in design software, designers can now use AI to generate prototypes based on text prompts. However, the effectiveness of this technology hinges on how specific those prompts are. Research indicates that detailed prompts lead to outputs that closely resemble human-made designs, while vague prompts result in inconsistent and poorly structured prototypes. Common issues with AI-generated designs include cluttered layouts, repeated elements, and counterintuitive content flow. For instance, AI often produces pages filled with unnecessary visual elements, making navigation difficult and increasing cognitive load for users. It also struggles with maintaining a logical sequence of information, leading to disjointed designs that fail to guide users effectively. Furthermore, AI tends to emphasize the wrong elements visually, which can confuse users about what’s most important on the page. To enhance AI-generated outputs, designers should focus on several strategies to improve prompt specificity. Using precise visual keywords helps clarify intent, while referencing established design styles can guide the AI toward the desired aesthetic. Lightweight visual references, like moodboards or screenshots, can also be effective when high-fidelity mockups are impractical. While these methods don’t guarantee perfect results, they can significantly improve the quality of AI-generated prototypes without requiring extensive design work upfront.