Conversational UI
Problem
Traditional interfaces with buttons, forms, and menus can feel rigid and require users to learn specific interaction patterns. Users often prefer natural language communication but struggle with AI that doesn't understand context or conversational nuances.
Solution
Create conversational interfaces that understand natural language, maintain context across interactions, and respond in a human-like manner. Design for both text and voice interactions, with appropriate personality and tone that matches your brand and user expectations.
Examples in the Wild
Slack AI Assistant
Integrates naturally into team conversations, understanding context and providing relevant assistance without disrupting workflow.
Interactive Code Example
Simple Conversational Bot Interface
This React component implements a conversational UI for a customer support bot that can answer questions, handle escalations to human agents, and maintain conversation context.
Toggle to code view to see the implementation details.
Implementation & Considerations
Implementation Guidelines
Use natural language patterns and avoid overly formal or robotic responses
Maintain conversation context and reference previous interactions appropriately
Provide clear conversation starters and example prompts for new users
Handle misunderstandings gracefully with clarifying questions
Use appropriate personality and tone that matches your brand
Support both structured commands and free-form natural language
Provide visual cues for conversation state (typing indicators, read receipts)
Design for both synchronous and asynchronous conversation patterns
Include conversation history and search functionality
Handle interruptions and topic changes smoothly
Design Considerations
Balance personality with professionalism based on use case
Consider cultural differences in communication styles and expectations
Plan for multilingual support and language detection
Design appropriate fallback mechanisms when AI doesn't understand
Consider privacy implications of conversation history storage
Account for accessibility needs in both text and voice interfaces
Plan for conversation handoffs between AI and human agents
Consider the cognitive load of extended conversations
Design appropriate boundaries for AI personality and capabilities
Test with diverse user groups to validate conversational patterns