ai-product-design

name	ai-product-design
description	Designing AI-powered features, managing user expectations, and AI transparency.
triggers	["AI design","AI UX","AI product","machine learning UX"]

AI Product Design

Core Principles

1. Set expectations: Tell users what AI can and cannot do
2. Show confidence: Indicate AI's certainty level when relevant
3. Allow override: Users can always correct or override AI decisions
4. Be transparent: Show how AI arrived at its output when possible
5. Fail gracefully: AI mistakes should be easy to spot and fix

Patterns

Pattern	Example
Suggestion	Email autocomplete, search suggestions
Classification	Spam detection, content categorization
Generation	Text, image, code generation
Prediction	Estimated delivery time, churn prediction
Automation	Auto-tagging, smart replies

AI Suggestion UX

• Show suggestion inline or as a separate element
• Accept: one tap/click or keyboard shortcut
• Reject: easy dismiss, don't re-suggest the same thing
• Edit: modify the suggestion before accepting
• Feedback: way to indicate if suggestion was helpful

AI Transparency

• 'AI-generated' label on AI content
• Confidence scores when relevant (but don't overwhelm)
• Source attribution for AI summaries
• Audit trail for AI decisions in business contexts