ai-interaction-patterns

Name: ai-interaction-patterns
Availability: InStock
Author: william189189

Provides UX/AI interaction patterns for onboarding, memory, prompts, and governance.

Updated Mar 26, 2026

Search Tags:#ai #memory #trust #human-in-the-loop #ux-patterns #ai-ux

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npx skills add https://github.com/William189189/boss-bidding --skill ai-interaction-patterns-william189189

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Please help me install this Agent Skill.
Skill: ai-interaction-patterns
Source: https://github.com/William189189/boss-bidding/tree/main/.claude/skills/25-ai-interaction-patterns
Command: npx skills add https://github.com/William189189/boss-bidding --skill ai-interaction-patterns-william189189

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AI teams often struggle to design AI-powered interfaces that balance usability, trust, and transparency; they need a centralized guide of repeatable patterns to reduce ambiguity and drift.

Core Features & Use Cases

Comprehensive catalog of AI interaction patterns across six categories: Wayfinders, Prompt Actions, Tuners, Governors, Trust Builders, and Identifiers.
Practical guidance for onboarding, prompt control, memory management, and human-in-the-loop governance, plus reference material for implementation.
Real-world scenario: apply these patterns to an AI-powered assistant in a customer-support workflow to improve clarity, trust, and controllability.

Quick Start

Show me a ready-to-use catalog of AI interaction patterns for AI UX design.

Frequently Asked Questions about ai-interaction-patterns

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What are AI interaction patterns for UX design and when do I need them?▼

AI interaction patterns are repeatable UX structures that balance usability, trust, and transparency in AI interfaces. You need them when designing onboarding, memory, prompts, or governance flows to reduce ambiguity and drift in AI-powered products.

How do I design human-in-the-loop governance for an AI assistant?▼

Design human-in-the-loop governance by applying Governor and Trust Builder patterns. These AI UX patterns provide structured control mechanisms for AI assistant workflows, ensuring users maintain oversight and clarity during automated customer-support or enterprise tasks.

Can I use these AI UX patterns for both enterprise and consumer products?▼

Yes, these AI interaction patterns apply across both enterprise and consumer products. The catalog covers six categories—Wayfinders, Prompt Actions, Tuners, Governors, Trust Builders, and Identifiers—offering scalable guidance for onboarding, memory management, and prompt control.

What's the best way to structure AI onboarding and prompt control in a user interface?▼

The best way to structure AI onboarding and prompt control is using Wayfinders and Prompt Actions patterns. These AI UX patterns guide users through initial interactions and provide clear, actionable prompt controls to improve interface clarity and trust.

How do I manage AI memory and transparency in UX design?▼

Manage AI memory and transparency by implementing Tuners and Identifiers patterns. These AI UX patterns help users understand what the system remembers, adjust AI behavior, and verify outputs, building sustained trust through visible system state and memory management.

Why does my AI interface lack user trust and how can I fix it?▼

AI interfaces lack trust when transparency and controllability are missing. Fix this by applying Trust Builder and Governor patterns from this AI UX catalog, which provide practical guidance for clarifying AI actions, managing memory, and enabling human oversight.