Are you looking to get the most out of large language models like LLaMA and GPT?
A new research paper introduces 26 guiding principles designed to help you ask better questions and create more effective prompts.
These principles aim to make interacting with AI easier and more intuitive. Whether you’re a developer or just curious about AI, these tips can help you communicate with these models in a more natural, human-like way. Let’s explore how these guidelines can enhance your AI experience!
Here’s a summary of the key principles:
Direct Communication: No need for politeness; skip phrases like “please” or “thank you.” 🚀
Audience Awareness: Tailor prompts to the intended audience, such as experts in the field. 🎓
Simplify Complexity: Break down complex tasks into a series of simpler prompts. 🧩
Affirmative Directives: Use ‘do’ instead of ‘don’t’ to encourage positive action. ✅
Seek Clarity: Use prompts for clarity, like "Explain [topic] in simple terms." 💡
Incentivize Solutions: Include statements like “I’m going to tip $xxx for a better solution.” 💰
Example-Driven: Implement few-shot prompting for better context and understanding. 📚
Structured Formatting: Use specific headings to structure prompts effectively. 📑
Clear Tasks: Incorporate phrases like “Your task is” and “You MUST.” 📝
Consequences: Mention “You will be penalized” for non-compliance. ⚠️
Natural Responses: Ensure responses are given in a natural, human-like manner. 🤖
Step-by-Step Thinking: Encourage models to “think step by step.” 🛤️
Avoid Stereotypes: Ensure answers are unbiased and free from stereotypes. 🌍
Elicit Details: Ask questions to gather necessary information for better responses. 🔍
Teach and Test: Use prompts like “Teach me the [topic] and include a test at the end.” 📖
Role Assignment: Designate roles for the language models to follow. 🎭
Delimiters: Use delimiters for clarity in prompts. 📏
Repetition for Emphasis: Repeat key words or phrases to reinforce focus. 🔄
Chain-of-Thought: Combine chain-of-thought with few-shot prompts for depth. 🌊
Output Primers: Conclude prompts with the beginning of the desired output. 🎯
Detailed Requests: Request detailed texts explicitly to ensure thoroughness. 📜
Revise with Care: Ask for revisions while maintaining original style. ✍️
Multi-File Management: For complex coding, generate scripts to handle multiple files. 🗂️
Text Continuation: Provide beginnings and ask for a continuation to maintain flow. 📖➡️
Clear Requirements: State requirements clearly in keywords or instructions. 📋
Language Consistency: Write in a style similar to the provided sample for coherence. ✨
Check out more in there paper here
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