Meta Prompting

Meta Prompting involves asking the language model for advice or suggestions on how to improve the current prompt to achieve better results.

This technique leverages the model’s own understanding of effective communication to help refine your prompting strategy. It’s like asking an expert for tips on how to better communicate with them.

Pros:

• Empowers users to refine their prompting strategies
• Leverages the model’s own understanding of effective communication
• Can lead to better results in subsequent attempts
• Helps users learn about prompt engineering through practical examples

Cons:

• The model’s suggestions might not always be optimal
• Suggestions may not be directly applicable to the specific task
• Requires user judgment and further experimentation
• Takes an extra step in the process

Example:

Prompt:

How can I improve this prompt to get a more creative story idea:
'Write a short story about a robot'?

Possible Expected Output:

You could try specifying the genre, the robot's personality, the setting, or a conflict. For example:
'Write a humorous short story about a clumsy robot trying to win a dance competition in a futuristic city.'

Meta prompting works best for:

• When you’re not getting the results you want but aren’t sure why
• Learning how to craft better prompts
• Exploring different approaches to a task
• When you want to understand what additional context might help
• Refining complex or specialized prompts

When you want to elicit responses with a specific tone or perspective, role play prompting can be an effective next step.