Ai Loading Ux

What it does

This skill, Ai Loading UX, provides design patterns and a decision framework to improve the user experience when users are waiting for AI-powered outputs. It focuses on how to visually represent different stages of AI processing—such as reasoning, multi-step task completion, content generation, or background processes—to build trust and reduce perceived wait times. The core principle is to provide appropriate feedback without overwhelming the user with unnecessary information.

When to use it

• When designing an agent workflow that involves AI reasoning (e.g., complex question answering).
• For tasks involving multiple sequential steps completed by the AI.
• During content generation where output is streamed token-by-token.
• When background processing occurs as part of a larger task.

Key capabilities

• Decision Framework: Categorizes waiting scenarios (Reasoning Display, Progress Steps, Streaming States, Status Indicators) to guide design choices.
• Pattern Categories: Offers specific design patterns for each category, with recommended approaches and anti-patterns.
• Core Principles: Emphasizes the "Elevator Mirror Effect," Progressive Disclosure, balancing transparency, and signaling completion clearly.
• Implementation Checklist: Provides a step-by-step guide for implementing AI loading states effectively.

Example prompts

• "What's the best way to show users that the AI is reasoning through a complex question?"
• "How should I visually represent progress when the AI is completing multiple steps in a task?"
• "I need to display content being generated token-by-token. What patterns are recommended?"

Tips & gotchas

• Consider the "Elevator Mirror Effect"—subtle animations can significantly reduce perceived wait times.
• Avoid overwhelming users with too much detail; use progressive disclosure to reveal information only when requested.
• Always signal completion clearly to avoid user frustration.