Step 4 of 7: From Idea to Impact
Every AI UX decision should answer one question first: does this help the user calibrate how much to trust the output? Confidence signaling, reversibility, and explainability aren't nice-to-haves layered on later. They're the actual design problem. Delight comes after trust, never before it.
Confidence display: don't show a number ("87% confident") to end users; it means nothing to them. Instead use tiered visual treatment: high-confidence outputs render as normal editable text, medium-confidence outputs get a subtle "review suggested" badge, low-confidence outputs don't render as a draft at all. They render as a prompt for the human to write from scratch with AI-surfaced context alongside.
Reversibility: every AI action needs an undo path with zero friction. For the dispute tool: the AI-drafted response is never sent automatically. It sits in a draft state, editable, with a visible diff against a blank response, until a human explicitly sends it.
Explainability: "AI suggested this because..." should point to specific evidence, not a generic disclaimer. For a dispute draft: highlight which transaction record, which policy clause, and which similar past case informed the suggestion, inline, not in a separate help panel nobody opens.
Graceful failure messaging: never show a blank state or generic error when the AI can't act. Show what it does know, with the relevant context pre-pulled.
2. Figma AI Prompt Patterns: the exact prompt for generating a confidence-aware component state machine, not a static mockup.
3. AI Feature Onboarding Flow: the 5-screen structure that builds trust muscle memory from the first interaction.
4. Worked Example: why raw confidence percentages backfired with real users, and what tripled genuine engagement instead.
5. Common Pitfalls: why designing the happy path first and retrofitting failure states is backwards for AI features.
6. Nuance Most Guides Skip: why progressive disclosure is a trust-building sequence for AI, not just an information architecture pattern.