Overview
How might we design ai capability explorer so people can trust and act on AI output?
When this pattern fits
- Perfect for AI-powered platforms, enterprise tools, and applications with extensive AI functionality where users need comprehensive feature discovery.
When to skip or lighten it
- Products with only one AI feature.
- Catalogs that rot because nobody owns updates.
- Explorer with no deep link into the actual feature.
States
State model coming soon
Key UX elements
Key UX elements coming soon
Anti-patterns to avoid
Static marketing list with broken try links.
No search or filter by task type.
Features listed that are beta without label.
Explorer only on marketing site, not in app.
How products use it
| Product | Implementation |
|---|---|
| ChatGPT | GPTs and tools directory with launch actions. |
| Claude | Feature and connector discovery in product help. |
| GitHub Copilot | Copilot feature hub in IDE and docs. |
| Adobe Firefly | Module browser for generative tasks. |
Implementation
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Generate a production-ready implementation of the "AI Capability Explorer" AI interface design pattern.
Pattern Definition:Frequently asked questions
What each entry needs?
Name, one-line outcome, example input, try button, and plan or permission badge.
Explorer vs feature discovery feed?
Explorer is browsable full catalog. Feed is personalized recommendations subset.
Keep fresh how?
Tie entries to feature flags and changelog; auto-hide unavailable items.
Search?
Natural language search across tasks, not only feature names.