TOPICS
I. Predictability, trust, explainability
- How do you create predictable UX when AI outputs are inherently unpredictable?
- What design patterns help users understand and trust non-deterministic responses?
- When should interfaces expose uncertainty vs. present confident responses?
- How do you design interfaces that build appropriate trust in AI systems?
- What’s the right balance between simplicity and explainability?
- How do you design interfaces that adapt without becoming unpredictable?
II. Interface paradigms & interaction models
- Will chat interfaces dominate, or will we see a proliferation of specialized interface types?
- What determines when to build a custom interface versus adopting chat paradigms?
- How do you balance familiar patterns with innovative interaction models?
- How do you design for both power users and newcomers in the same interface?
- When does customization enhance vs. complicate the user experience?
III. Personalization, consistency, design systems
- How are traditional design systems evolving to accommodate AI-driven interfaces?
- What new components and patterns are essential for AI product design?
- How do you maintain consistency when AI enables more personalized experiences?
- How do you balance personalized AI experiences with consistent design systems?
IV. Org change, skills, team dynamics
- How has AI changed the relationship between design, engineering, and product teams?
- What new skills and processes are needed for effective AI product development?
- How do you maintain design quality when AI capabilities evolve rapidly?
- What design decisions help users maintain agency in AI-assisted workflows?