The PhotoGenius mobile app uses a voice-first, conversational interface for nuanced photo editing commands like 'make me smile slightly without teeth'. This signals a potential paradigm shift in UX for creative tools, moving away from complex menus and sliders towards natural language interaction.
Figma CEO Dylan Field predicts we will look back at current text prompting for AI as a primitive, command-line interface, similar to MS-DOS. The next major opportunity is to create intuitive, use-case-specific interfaces—like a compass for AI's latent space—that allow for more precise control beyond text.
Current text-based prompting for AI is a primitive, temporary phase, similar to MS-DOS. The future lies in more intuitive, constrained, and creative interfaces that allow for richer, more visual exploration of a model's latent space, moving beyond just natural language.
The true evolution of voice AI is not just adding voice commands to screen-based interfaces. It's about building agents so trustworthy they eliminate the need for screens for many tasks. This shift from hybrid voice/screen interaction to a screenless future is the next major leap in user modality.
Most generative AI tools get users 80% of the way to their goal, but refining the final 20% is difficult without starting over. The key innovation of tools like AI video animator Waffer is allowing iterative, precise edits via text commands (e.g., "zoom in at 1.5 seconds"). This level of control is the next major step for creative AI tools.
While most focus on human-to-computer interactions, Crisp.ai's founder argues that significant unsolved challenges and opportunities exist in using AI to improve human-to-human communication. This includes real-time enhancements like making a speaker's audio sound studio-quality with a single click, which directly boosts conversation productivity.
The best agentic UX isn't a generic chat overlay. Instead, identify where users struggle with complex inputs like formulas or code. Replace these friction points with a native, natural language interface that directly integrates the AI into the core product workflow, making it feel seamless and powerful.
The magic of ChatGPT's voice mode in a car is that it feels like another person in the conversation. Conversely, Meta's AI glasses failed when translating a menu because they acted like a screen reader, ignoring the human context of how people actually read menus. Context is everything for voice.
The next frontier for conversational AI is not just better text, but "Generative UI"—the ability to respond with interactive components. Instead of describing the weather, an AI can present a weather widget, merging the flexibility of chat with the richness of a graphical interface.
Open-ended prompts overwhelm new users who don't know what's possible. A better approach is to productize AI into specific features. Use familiar UI like sliders and dropdowns to gather user intent, which then constructs a complex prompt behind the scenes, making powerful AI accessible without requiring prompt engineering skills.
The initial fortune-telling app was too generic. By providing simple, natural language feedback like "make it kid-friendly" and "more concrete," the developer iteratively guided the AI to produce a more suitable user experience without writing a single line of code.