Instead of being limited by off-the-shelf software, designers can dramatically accelerate their process by building bespoke tools. MDS used the AI tool V0 to create a custom bitmap icon builder, enabling rapid prototyping of a unique interactive element.

Instead of accepting default AI designs, proactively source superior design elements. Use pre-vetted Google Font combinations for typography and find specific MidJourney 'style reference' codes on social platforms like X to generate unique, high-quality images that match your desired aesthetic.

To enable AI agents to effectively modify your front-end, you must first remove global CSS files. These create hidden dependencies that make simple changes risky. Adopting a utility-first framework like Tailwind CSS allows for localized, component-level styling, making it vastly easier for AI to understand context and implement changes safely.

Instead of providing a vague functional description, feed prototyping AIs a detailed JSON data model first. This separates data from UI generation, forcing the AI to build a more realistic and higher-quality experience around concrete data, avoiding ambiguity and poor assumptions.

AI tools that generate functional UIs from prompts are eliminating the 'language barrier' between marketing, design, and engineering teams. Marketers can now create visual prototypes of what they want instead of writing ambiguous text-based briefs, ensuring alignment and drastically reducing development cycles.

The panel suggests a best practice for AI prototyping tools: focus on pinpointed interactions or small, specific user flows. Once a prototype grows to encompass the entire product, it's more efficient to move directly into the codebase, as you're past the point of exploration.

Leverage AI as an idea generator rather than a final execution tool. By prompting for multiple "vastly different" options—like hover effects—you can review a range of possibilities, select a promising direction, and then iterate, effectively using AI to explore your own taste.

The true creative potential for AI in design isn't generating safe, average outputs based on training data. Instead, AI should act as a tool to help designers interpolate between different styles and push them into novel, underexplored aesthetic territories, fostering originality rather than conformity.

AI coding tools generate functional but often generic designs. The key to creating a beautiful, personalized application is for the human to act as a creative director. This involves rejecting default outputs, finding specific aesthetic inspirations, and guiding the AI to implement a curated human vision.