vision-exploration

To explore potential future states using divergent thinking, you can run an AI-driven vision exploration process that identifies user values and motivations to generate 4-6 distinct end-game vision designs from a minimum viable concept, without technical constraints.

The best way to trace user motivations during product evolution is to use a visioning approach that identifies underlying problems and natural evolution pathways. This derives a trajectory from a minimum viable concept to ultimate potential, free from technical limitations.

Yes, you can generate multiple distinct end-game scenarios from a vague product idea. Vision exploration provides 4-6 unique final vision designs, offering different perspectives and interactions by focusing on open-ended, divergent future thinking rather than immediate feasibility.

No, vision exploration does not require technical feasibility constraints. It deliberately removes technical limitations to encourage open-ended divergent thinking, allowing you to derive a natural evolutionary pathway from a minimum viable concept to its ultimate potential state.

To start visioning the evolution of a current feature, run the skill to explore potential future pathways. It identifies user values and motivations to derive a natural evolution pathway, ultimately generating 4-6 distinct end-game vision designs with unique perspectives.