ai-interaction-patterns

AI interaction patterns are reusable UX design solutions for challenges in AI applications like onboarding, conversation flows, trust management, and memory context. This catalog provides 60+ structured patterns across six categories to guide safe, intuitive AI interface development.

Design trust management and disclosure patterns using the Trust Builders category in this catalog. It provides reference implementations for citations, transparent AI disclosures, and consistent avatar decisions to help users understand AI limitations and build confidence.

Structure onboarding flows for enterprise AI copilots using the pattern selection framework included in the catalog. It provides governance guidance and structured Markdown references to help you draft starter pattern recommendations for introducing new AI assistants in products.

Yes, you can use these AI UX patterns for mobile and voice chat assistants. The catalog supports pattern discovery and practical implementation across web, mobile, and voice channels for chat assistants, AI copilots, and enterprise AI UIs.

Manage memory and context persistence in AI conversation flows using the catalog's Governors and Tuners pattern categories. These provide best practices and reference implementations for maintaining memory context, prompt actions, and ongoing conversation governance.

Avoid using a pattern catalog for AI interaction design if your project requires highly customized, novel interface solutions outside standard chat, copilot, or enterprise UI paradigms, as the catalog focuses on established pattern discovery and governance for known AI UX challenges.