Chatbot AI UX patterns
Patterns for conversational surfaces: composers, streaming replies, memory, follow-ups, and recovery when a turn goes wrong. Pair with the Chat UX framework for territories and anti-patterns.
Related framework: Chat UX framework
Start here
Core patterns for chatbot UX.
13 patterns
Chat Artifacts
Side panel for content
Thread Branching
Edit and fork chats
Regeneration Carousel
Swipe bot responses
Response Refinement
Modify AI responses with contextual actions
Conversation History Search
Search through past conversations
Message Pinning
Pin important messages
Conversation Tags & Labels
Organize conversations with tags
Export Conversation
Export chats as PDF/Markdown/JSON
Conversation Templates
Save and reuse conversation starters
Turn Ownership Indicator
Shows who currently has the turn
Interrupt and Resume
Stop mid-response and continue with context
Memory Scope Toggle
Set memory persistence per message
Repair Contract
Retry with explicit delta and constraints
Frequently asked questions
When should I start with chatbot patterns?
Start here when your primary surface is a thread or composer. Prioritize turn-taking, streaming, and repair flows before visual polish—most chat failures come from unclear state, not styling.
How do chatbot patterns relate to the Chat UX framework?
Framework pages name territories (composer, memory, repair). Pattern pages are the catalog entries you implement, often with interactive demos and product examples from ChatGPT, Claude, and similar products.
What is the difference between streaming and status steps?
Streaming shows the answer appearing token-by-token. Status steps expose tool calls, retrieval, or reasoning traces—use both when users need progress during long waits and provenance when they expand the trace.
How do I spec memory and context for chat?
Use memory-management and context patterns so users see what is remembered, can edit or delete it, and understand scope per thread versus account. Hidden memory erodes trust when the model surprises users with stale facts.
Which chatbot patterns reduce abandonment after a bad reply?
Follow-up chips, regeneration, response refinement, and error-recovery patterns give users a low-friction next action instead of restarting the thread. Pair with clear interrupt/resume when generation can be stopped safely.
Can I search this category by product?
Yes—use the grid search or open individual patterns; each entry lists example products where that convention appears in production.