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AI UX patterns. Use for prompt UX, wayfinding, HITL, trust, disclosure, AI identity, memory UX, generative UI.
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Based on SOC occupation classification
Kailash DataFlow - zero-config data operations framework with automatic model-to-node generation and Data Fabric Engine. Use when asking about 'database operations', 'DataFlow', 'database models', 'CRUD operations', 'bulk operations', 'database queries', 'database migrations', 'multi-tenancy', 'multi-instance', 'database transactions', 'PostgreSQL', 'MySQL', 'SQLite', 'MongoDB', 'pgvector', 'vector search', 'document database', 'RAG', 'semantic search', 'existing database', 'database performance', 'database deployment', 'database testing', 'TDD with databases', 'external data sources', 'data products', 'db.source', 'db.product', 'db.start', 'fabric engine', 'source adapters', 'REST source', 'webhooks', or 'data fabric'. DataFlow is NOT an ORM - it generates 11 workflow nodes per SQL model, 8 nodes for MongoDB, and 3 nodes for vector operations.
Kailash Nexus - zero-config multi-channel platform for deploying workflows as API + CLI + MCP simultaneously. Use when asking about 'Nexus', 'multi-channel', 'platform deployment', 'API deployment', 'CLI deployment', 'MCP deployment', 'unified sessions', 'workflow deployment', 'production deployment', 'API gateway', 'session management', 'health monitoring', 'enterprise platform', 'plugins', 'event system', or 'workflow registration'. Also covers K8s integration: 'K8s probes', 'healthz', 'readyz', 'startup probe', 'ProbeManager', 'ProbeState', 'OpenAPI', 'openapi.json', 'OpenApiGenerator', 'security headers', 'CSRF middleware', 'CSRFMiddleware', 'SecurityHeadersMiddleware', 'middleware presets', 'Preset', or 'HSTS'.
Kailash Kaizen - production-ready AI agent framework with signature-based programming, multi-agent coordination, and enterprise features. Use when asking about 'AI agents', 'agent framework', 'BaseAgent', 'multi-agent systems', 'agent coordination', 'signatures', 'agent signatures', 'RAG agents', 'vision agents', 'audio agents', 'multimodal agents', 'agent prompts', 'prompt optimization', 'chain of thought', 'ReAct pattern', 'Planning agent', 'PEV agent', 'Tree-of-Thoughts', 'pipeline patterns', 'supervisor-worker', 'router pattern', 'ensemble pattern', 'blackboard pattern', 'parallel execution', 'agent-to-agent communication', 'A2A protocol', 'streaming agents', 'agent testing', 'agent memory', 'agentic workflows', 'AgentRegistry', 'OrchestrationRuntime', 'distributed agents', 'agent registry', '100+ agents', 'capability discovery', 'fault tolerance', 'health monitoring', 'trust protocol', 'EATP', 'TrustedAgent', 'trust chains', 'secure messaging', 'enterprise trust', 'credential rotation', 'trust verificati
Kailash cheatsheets: patterns, nodes, workflows, cycles, performance, security, multi-tenancy, saga, custom nodes.
Kailash dev guides: custom nodes, MCP, async, testing, deployment, RAG, security, monitoring, SDK internals.
Workflow templates: finance, healthcare, logistics, manufacturing, retail, ETL, RAG, document processing, API.
| name | ai-interaction-patterns |
| description | AI UX patterns. Use for prompt UX, wayfinding, HITL, trust, disclosure, AI identity, memory UX, generative UI. |
AI-specific UX patterns for designing interfaces where users interact with AI models. Covers the full interaction lifecycle: from first prompt to output verification, memory persistence, and trust building.
Source: Based on Shape of AI pattern library (CC-BY-NC-SA) by Emily Campbell.
Use these patterns when asking about AI UX, AI interaction, prompt UX, AI trust, AI disclosure, AI avatar, AI personality, AI memory UX, action plan UX, stream of thought, AI citations, AI controls, AI wayfinding, AI suggestions, gallery pattern, follow-up pattern, draft mode, AI variations, AI consent, AI caveat, human-in-the-loop, AI transparency, AI state, prompt design, AI onboarding, or generative UI.
| Skill | Focus |
|---|---|
| 23-uiux-design-principles | Layout, hierarchy, responsive design (framework-agnostic) |
| 21-enterprise-ai-ux | Enterprise context: challenge taxonomy, professional palettes, RBAC |
| 22-conversation-ux | Thread management, branching data model, context switching |
| 20-interactive-widgets | Widget protocols, rendering pipeline, state management |
| 25-ai-interaction-patterns (this) | AI-SPECIFIC interaction logic: how users prompt, control, trust, and relate to AI |
| User Says/Feels | Apply Pattern |
|---|---|
| "I don't know what to ask" | Gallery, Suggestions, Templates |
| "AI didn't understand me" | Follow-ups, Nudges, Prompt Enhancer |
| "I want alternatives" | Variations, Branches, Randomize |
| "Is this accurate?" | Citations, References, Caveat |
| "This is taking too long" | Draft Mode, Controls, Cost Estimates |
| "I need AI to do something complex" | Action Plan, Stream of Thought |
| "Is this AI or human?" | Disclosure, Avatar, Name |
| "Don't store my data" | Incognito Mode, Consent, Data Ownership |
| "AI forgot what I said" | Memory (scoped/global/ephemeral) |
| Product Type | Essential Patterns | Nice-to-Have |
|---|---|---|
| Chat assistant | Open Input, Suggestions, Follow-ups, Memory, Disclosure | Gallery, Voice & Tone, Branches |
| Code copilot | Inline Action, Stream of Thought, Controls, Citations | Action Plan, Draft Mode |
| Image generator | Gallery, Parameters, Variations, Inpainting, Preset Styles | Draft Mode, Randomize |
| Document AI | Attachments, Citations, Caveat, Disclosure, Summary | Transform, Expand, Follow-ups |
| AI agent | Action Plan, Controls, Verification, Stream of Thought, Cost Estimates | Memory, Consent |
| Voice assistant | Voice Avatar, Personality, Controls, Disclosure | Memory, Consent |
| Enterprise analytics | Citations, Connectors, Filters, Modes, Disclosure | Action Plan, Memory |
High-stakes domain (healthcare, finance, legal)?
YES -> CRITICAL: Citations + Verification + Disclosure + Caveat + Audit
NO -> AI output mixed with human content?
YES -> HIGH: Disclosure + Citations + Caveat
NO -> Could AI output cause harm if wrong?
YES -> MEDIUM: Caveat + Citations (optional)
NO -> LOW: Minimal caveat, focus on UX quality
Gallery, Suggestions, Templates, Follow-ups, Initial CTA, Nudges, Prompt Details, Randomize
Open Input, Inline Action, Chained Action, Regenerate, Transform, Restyle, Expand, Summary, Synthesis, Describe, Auto-fill, Restructure, Madlibs, Inpainting
Attachments, Connectors, Parameters, Model Management, Modes, Filters, Prompt Enhancer, Preset Styles, Saved Styles, Voice and Tone
Action Plan, Stream of Thought, Controls, Draft Mode, Branches, Variations, Citations, References, Verification, Memory, Cost Estimates, Sample Response, Shared Vision
Disclosure, Caveat, Consent, Data Ownership, Watermark, Footprints, Incognito Mode
Avatar, Personality, Name, Color, Iconography
| Rule | Why |
|---|---|
| NEVER use photorealistic avatars unless AI matches that capability | Sets unrealistic expectations, erodes trust |
| ALWAYS show Stream of Thought for tasks > 5 seconds | Users abandon when they can't see progress |
| NEVER let Memory be a black box | Users must see, edit, and delete what AI remembers |
| ALWAYS offer Controls (at minimum: stop) during generation | Users need escape hatches |
| NEVER rely solely on Caveats for safety | Caveat blindness is real; design the system to be safe |
| ALWAYS distinguish AI content from human content in blended UIs | Users may unknowingly present AI work as their own |
| NEVER overwrite user work without Verification | Accidental overwrites destroy trust instantly |
uiux-designer - AI-specific interaction pattern selection and designkaizen-specialist - AI agent capabilities informing UX decisionsreact-specialist - Implementation of AI interaction patterns