Fellowmind: AI agent library visualization
- Client
- Fellowmind
- My role
- UX/UI
- Project time
- Ongoing
- Tools
- Figma, Miro
- Focus
- User experience, visual design
Given a rapid timeline and the pioneering nature of AI agent marketplaces, we adopted a hypothesis-driven approach. With few established patterns to follow, I visualized an initial “favorites” cart system based on e-commerce patterns as a starting point.
This work focused on getting a functional user journey—listing, detail view, and selection—in front of users quickly. While the flow is an early iteration, it establishes a clear baseline for us to track engagement, validate the mental model, and onboard the client to an experimentation mindset for future refinements.
Key takeaways
Borrow proven patterns
With few established patterns for AI agent marketplaces, familiar e-commerce patterns like a favourites cart gave users a credible starting point.
Ship early to learn
Getting listing, detail view and selection in front of users quickly created a baseline to measure engagement and validate the mental model.
Build an experimentation mindset
The first iteration also brought the client into a habit of testing and refining over time.
