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AI UX Design Patterns

How the world's best AI products design their experiences, documented, analyzed, and continuously updated.

Patterns used by leading companies

Score your AI interface against 36 proven UX patterns

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The AI UX design pattern library for product designers and teams building AI-powered experiences. Each pattern is documented from 3+ real implementations across products like ChatGPT, Claude, GitHub Copilot, Midjourney, Google, and Notion, with examples, code demos, and research-backed guidance you can apply today.

Categories

Contextual Assistance

Offer timely, proactive help and suggestions based on user context, history, and needs.

Human-AI Collaboration

Progressive Disclosure

Gradually reveal information, options, or AI features to reduce cognitive load and simplify complex tasks.

Natural Interaction

Human-in-the-Loop

Balance automation with human oversight for critical decisions, ensuring AI augments human judgment.

Human-AI Collaboration

Explainable AI (XAI)

Make AI decisions understandable via visualizations, explanations, and transparent reasoning.

Trustworthy & Reliable AI

Conversational UI

Design intuitive, engaging, human-like interactions via chat and voice interfaces.

Natural Interaction

Adaptive Interfaces

Interfaces that learn user behavior and automatically adjust layout and functionality to match individual usage patterns.

Adaptive & Intelligent Systems

Multimodal Interaction

Combine voice, touch, gesture, text, and visual input for natural interaction.

Natural Interaction

Guided Learning

Break complex tasks into guided steps, adapting to user knowledge levels.

Adaptive & Intelligent Systems

Augmented Creation

Empower users to create content with AI as a collaborative partner.

Human-AI Collaboration

Responsible AI Design

Prioritize fairness, transparency, and accountability throughout AI lifecycle.

Trustworthy & Reliable AI

Error Recovery & Graceful Degradation

Fail gracefully with clear recovery paths when things go wrong.

Trustworthy & Reliable AI

Collaborative AI

Enable effective collaboration between multiple users and AI within shared workflows.

Human-AI Collaboration

Ambient Intelligence

Create unobtrusive AI that senses context and provides assistance without explicit interaction.

Adaptive & Intelligent Systems

Safe Exploration

Provide sandbox environments for experimenting with AI without risk.

Trustworthy & Reliable AI

Predictive Anticipation

AI that predicts user needs before they're expressed, pre-loading content and suggesting next actions based on behavioral patterns.

Adaptive & Intelligent Systems

Confidence Visualization

Display AI certainty levels through visual indicators, helping users understand prediction reliability and decide when to trust or verify outputs.

Trustworthy & Reliable AI

Feedback Loops

Continuous learning mechanisms where user corrections and preferences improve AI performance, creating experiences that evolve with usage.

Human-AI Collaboration

Graceful Handoff

Seamless transitions between AI automation and human control.

Human-AI Collaboration

Context Switching

Smooth transitions between tasks or topics while maintaining conversation continuity.

Natural Interaction

Intelligent Caching

Pre-fetch and cache AI content for instant results, reducing latency.

Performance & Efficiency

Progressive Enhancement

Provide immediate basic responses then progressively add detail and accuracy.

Performance & Efficiency

Privacy-First Design

Minimize data collection and provide transparent privacy controls.

Privacy & Control

Selective Memory

Control what AI remembers, forgets, or ignores with transparent settings.

Privacy & Control

Universal Access Patterns

Ensure equitable access for all abilities, languages, and assistive technologies.

Accessibility & Inclusion

Crisis Detection & Escalation

Detect crisis signals and immediately provide professional resources.

Safety & Harm Prevention

Session Degradation Prevention

Strengthen safety checks during extended conversations with session limits.

Safety & Harm Prevention

Anti-Manipulation Safeguards

Detect actual harmful intent beyond surface framing regardless of how it's disguised

Safety & Harm Prevention

Vulnerable User Protection

Detect vulnerable users and apply graduated age, crisis, and dependency protections.

Safety & Harm Prevention

Autonomy Spectrum

Provide a spectrum of autonomy levels - from passive suggestions to full autonomy - that users can adjust per task type, enabling granular control over how independently an AI agent operates.

Human-AI Collaboration

Intent Preview

Before any significant action, the agent presents a clear, scannable summary of what it intends to do - showing planned steps, reversibility status, and edit controls for user approval.

Human-AI Collaboration

Plan Summary

Provide a structured breakdown of the agent's reasoning and approach - showing goal interpretation, strategy, subtask checklist, and assumptions - so users can evaluate the plan before execution begins.

Trustworthy & Reliable AI

Action Audit Trail

Provide a timestamped, structured log of every action the agent took - grouped by task, with reversibility status, selective undo, and diff views - so users can review and correct agent behavior after the fact.

Trustworthy & Reliable AI

Escalation Pathways

Design structured escalation triggers and handoff mechanisms so agents can pause and ask for human guidance when they encounter ambiguity, conflicts, or decisions beyond their authorization - without breaking workflow or losing context.

Human-AI Collaboration

Trust Calibration

Design a system that progressively builds appropriate trust through demonstrated competence - showing track records per domain, celebrating milestones, and adjusting oversight based on actual agent performance.

Trustworthy & Reliable AI

Mixed-Initiative Control

Design interaction models where control flows seamlessly between human and agent - supporting parallel work zones, interruptible agent activity, and natural handoffs without formal 'take over' actions.

Human-AI Collaboration

Agent Status & Monitoring

Design a layered status system with escalating attention demands - from ambient badges to glanceable progress panels to interrupting notifications - so users stay informed about agent activity without being forced to watch.

Performance & Efficiency

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AI UX patterns from shipped products. Demos, code, and real examples.

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