Contrary to the belief that AI leads to a loss of creative control, designers can achieve their exact vision by giving specific, detailed instructions. The AI acts as a hyper-competent collaborator, not an autonomous creator, allowing for meticulous refinement of the final product.
When using AI for development, designers can bypass the traditional Figma-to-code workflow. Figma becomes a specialized tool for the final 20% of the project, used to generate CSS for complex visual details that are difficult to articulate in a text prompt.
AI lowers the technical barrier to building products, making design taste and judgment the critical differentiators. An AI can execute tasks, but it requires a designer's discerning eye to guide it toward a high-quality, cohesive, and valuable user experience.
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.
While AI can rapidly scaffold a functional application, the most time-consuming phase is the final 20% of work. This involves refining UI details, handling numerous edge cases, and achieving a high level of polish, which requires meticulous back-and-forth and debugging.
A designer, initially resistant to AI's encroachment on his craft, shifted perspective. He stopped seeing AI as a devaluing replacement and began viewing it as a powerful tool to enhance his existing skills and enter new domains like product building.
Instead of just executing known tasks, use AI to explore the feasibility of complex features. By asking "what's the best way to do this?", the AI provides a ranked list of technical approaches, complete with pros and cons, which helps to de-risk development.
When using AI for development, don't pretend to understand technical concepts. By stating knowledge gaps directly in the prompt (e.g., "I don't know Terminal"), the AI provides more accessible and actionable guidance, avoiding jargon and breaking down complex steps.
Tasks like adding sound effects, once requiring specialized skills, can now be handled directly by designers using AI. Prompting for sound options for specific actions allows for rapid prototyping and implementation, integrating audio into the core UX design process.