Patterns are based on our 200+ real-world examples,
organized across five phases of the product journey.
Onboarding
Entry touchpoints
Entryways that show users how to begin; search, suggested prompts, open input, icons, proactive nudges, or autocomplete.
Free
NewProactive suggestions
Surface context-aware suggestions that guide users to the most useful action or question to ask next.
Entry touchpoints
Open input
Offer a flexible chat-style input so users can express needs naturally.
Entry touchpoints
Icons
Use recognizable AI icons (e.g., sparkles) to indicate AI-powered actions and areas.
Entry touchpoints
Suggested prompts
Provide starter prompts that showcase range and help users get unstuck.
Entry touchpoints
Searching & filtering
Help users explore what AI can do directly from search and filtering experiences.
Entry touchpoints
Autocomplete
Predict and complete inputs to reduce effort and nudge users toward effective prompts.
Setting expectations
The system frames its role, boundaries, and personality through concise notes and brand/tone.
Setting expectations
Disclaimer
Set expectations with concise notes about capabilities, limits, and appropriate use.
Setting expectations
Branding & tone
Use branding and tone to set the AI’s personality and expectations.
Input
Expressive Input
Ways for users to express intent; voice, images, handwriting, gestures, or structured prompts.
Expressive Input
Visual input
Let users attach images, screenshots, or other visuals as part of the request.
Expressive Input
Gesture input
Allow gesture-based inputs (touch, gestures) where applicable for natural interactions.
Expressive Input
Prompt builder
Offer lightweight structure (slots, hints) to compose clearer prompts faster.
Expanding context
Additional signals that enrich the request; prompt help, model choice, connectors, or knowledge sources.
Expanding context
Prompt assistance
Suggest improvements and show a quick preview of likely output to confirm direction.
Expanding context
Model selection
Let users pick the right model or mode for the task when it matters.
Expanding context
MCP connectors
Connect to tools and data sources so AI can act with relevant information.
Expanding context
Knowledge base
Use organizational knowledge (MCPs, docs, wikis) to specialize responses.
Output
Types of outputs
Different ways responses are delivered; previews, video, images, audio, summaries, or structured formats.
Types of outputs
Preview output
Show a preview of the output before it’s generated to help users understand what to expect.
Types of outputs
Video output
Generate or assemble video for dynamic explanations and demos.
Types of outputs
Image output
Return images or generated visuals as the primary output form.
Types of outputs
Audio output
Speak results aloud for accessibility and hands-free use.
Types of outputs
Variations
Provide multiple alternatives so users can choose the best fit.
Types of outputs
Multi-modal output
Combine text, images, audio, and video where appropriate for richer responses.
Types of outputs
Summarize
Condense long content into concise takeaways or executive summaries.
Types of outputs
Structured output
Return structured data (tables, JSON, steps) to make results actionable and machine-readable.
Processing
How the system handles generation; real-time, streaming, listening, parallel work, or stepwise updates.
Pro Exclusive
NewParallel processing
Run multiple candidates or tasks concurrently to speed up complex jobs.
Processing
Real-time
Return immediate answers when latency matters.
Processing
Streaming
Send partial or streaming results as they become available for faster perceived responsiveness.
Processing
Listening
Keep an open channel for incoming context (e.g., continuous audio or live inputs) as needed by the flow.
Processing
Processing steps
Show progress through distinct steps so users understand what’s happening.
Explainability
Help users understand answers and recover gracefully when things go wrong.
Explainability
Confidence indicators
Communicate certainty to help users judge reliability.
Explainability
Citations
Show sources and references to build trust.
Explainability
Error Recovery
Offer clear remediation when outputs fail. Explain issues and suggest fixes or retries.
Refinement
Correction & Iteration
Tools for revising outputs — continue, retry, act inline, edit visually, or review results.
Pro Exclusive
NewInline actions
Expose quick actions directly on content (rewrite, summarize, translate, etc.).
Correction & Iteration
Reply
Continue the conversation to refine results with follow-up instructions.
Correction & Iteration
Regenerate
Request a fresh attempt with the same or tweaked prompt.
Correction & Iteration
Review
Enable reviewing outputs to either accept them in one go or with revisions.
Learning
Managing memory
The system recalls, persists, or forgets context to support continuity and control.
Managing memory
Managing memory
Anticipate needs by recalling preferences and past interactions at the right time; store durable context while respecting user control.
Collecting feedback
Collect feedback to improve outputs and personalize future interactions.
Collecting feedback
Ratings / Thumbs up down
Capture quick sentiment on results to steer quality.
Collecting feedback
User rating
Allow detailed ratings or comments where nuance helps training.
Collecting feedback
Choose a response
Offer multiple answers and let users select the best to reinforce preferences.
Personalization
Adjust behavior, tone, and defaults to fit the individual user.
Personalization
Personalization
Tailor tone, suggestions, and defaults based on user history and choices.
Insights in your inbox, monthly
Stay ahead of the curve
for designers and product teams in the new AI paradigm.
