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Natural Interaction

Context Switching

Smooth transitions between tasks or topics while maintaining conversation continuity.

What is Context Switching?

Context Switching is an AI pattern that enables smooth transitions between tasks or topics without losing information. Instead of starting fresh each time, the AI maintains separate threads for different contexts. It's essential for multitasking professionals or anyone using AI across multiple projects. Examples include ChatGPT's conversation threads, Notion AI understanding your workspace, or Siri remembering your shopping list while helping with calendar events.

Problem

Users frequently switch between different tasks, topics, or projects when working with AI systems, but lose context and have to repeat information each time they switch. This creates friction and reduces productivity.

Solution

Implement intelligent context management that tracks multiple conversation threads, remembers relevant information for each context, and provides seamless transitions between different topics while maintaining continuity within each context.

Real-World Examples

Implementation

AI Design Prompt

Guidelines & Considerations

Implementation Guidelines

1

Maintain conversation history across sessions with clear visual indicators of context boundaries

2

Allow users to explicitly save and name different contexts for easy switching

3

Provide visual cues when context changes to avoid confusion about what the AI remembers

4

Implement smart context summarization to avoid overwhelming users with full history

5

Enable users to merge or split contexts when tasks overlap or diverge

6

Store context preferences locally first, syncing to cloud only with user permission

Design Considerations

1

Privacy concerns when storing conversation history across multiple contexts

2

Memory and storage limitations when maintaining extensive context across sessions

3

Potential for context confusion when switching rapidly between similar tasks

4

Need to balance context retention with the ability to start fresh conversations

5

Computational cost of maintaining and retrieving multiple active contexts

6

Risk of surfacing outdated or irrelevant information from previous contexts

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Related Patterns

Selective Memory
Conversational UI
Adaptive Interfaces
Previous PatternGraceful HandoffView All PatternsNext PatternIntelligent Caching

About the author

Imran Mohammed is a product designer who studies how the best AI products are designed. He studies and documents AI/UX patterns from shipped products (36 and counting) and is building Gist.design, an AI design thinking partner. His weekly analysis reaches thousands of designers on Medium.

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