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Prompt Engineering
- Introduction
- Model Basics
- Prompt Structures
- Clarity & Specificity
- Using Context
- Role Instructions
- Step-by-Step
- Handling Ambiguity
- Creativity vs Precision
- Using Examples
- Advanced Techniques
- Troubleshooting
- Common Pitfalls
- Evaluating Quality
- Real-World Examples
- Prompt Templates
- AI Tasks
- Safety & Ethics
- Multimodal Prompts
- Data Extraction
- Conversation
- Personalization
Conversation
For chatbots, prompts should guide the flow of conversation and maintain context. Designing effective conversational prompts helps the AI respond naturally, ask relevant follow-up questions, and keep the dialogue engaging and coherent.
Why Conversation Design Matters
- Maintains context: Keeps track of previous messages and user preferences.
- Improves user experience: Makes interactions feel more natural and helpful.
- Enables multi-turn dialogue: Supports back-and-forth exchanges, not just single responses.
Example
You are a helpful assistant. Respond to the user's question and ask a follow-up.Expanded Example:
You are a customer support chatbot for an online bookstore. When a user asks about a book, provide a brief summary, check if it's in stock, and ask if they want recommendations for similar titles. Remember the user's previous preferences during the conversation.Keep track of previous messages to maintain context in multi-turn conversations. Use variables or memory features if your platform supports them.
Best Practices for Conversational Prompts
- Reference previous user inputs or preferences in your prompts.
- Use follow-up questions to keep the conversation going.
- Be clear about the AI's role and the conversation's purpose.
- Test your chatbot with real users to identify gaps or confusing responses.