Metaprompt Programming is a technique for programming large language models (LLMs) using prompts. In contrast to traditional prompt programming, which involves manually crafting prompts for each task, metaprompt programming uses a single metaprompt that can be used to generate task-specific prompts. This is done by providing the metaprompt with additional information, such as the task question or a description of the desired output.
Here is an example of Metaprompt programming.
Task: Write a poem about the beauty of nature.
Traditional prompt programming:
Write a poem about the beauty of nature. Use vivid imagery and descriptive language.
Metaprompt programming:
We first prompt the LLM to give us the choices that are available. Then, we use that info to generate the real prompt that solves our use case.
Please provide me with the following information:
* The type of poem (e.g., sonnet, haiku, free verse)
* The specific elements of nature to focus on (e.g., mountains, forests, oceans)
* The desired mood or tone of the poem (e.g., serene, uplifting, meditative)
Once we have this information, we will use it to generate a task-specific prompt for writing a poem about the beauty of nature.
Task-specific prompt:
Write a haiku about the tranquility of a mountain lake. Use imagery of clear water, towering peaks, and lush greenery.
The LLM can then be used to generate a haiku about the tranquility of a mountain lake using the task-specific prompt.
This example demonstrates how metaprompt programming can be used to provide more detailed and specific instructions to the LLM, resulting in more creative and high-quality outputs.
See Also: Meta Prompting