Meta Prompting

Pre-Flight Briefing

Abstracting the Structure

Meta Prompting is an advanced prompting technique that focuses on the structural and syntactical aspects of tasks and problems rather than their specific content details.

Instead of providing heavy, content-driven examples (like in few-shot prompting), you provide the LLM with an abstract template or 'Solution Structure'.

According to Zhang et al. (2024), this approach has massive advantages: it is highly token-efficient because you don't waste tokens on long examples, and it provides a versatile framework.

Meta prompting works best when the LLM already has innate knowledge about the task, allowing it to leverage its zero-shot capabilities while strictly adhering to your structural roadmap.

Reference Examples

Structure-Oriented (Meta Prompting)

Problem: [question]
Solution Structure:
1. Begin with 'Let's think step by step.'
2. Follow with logical reasoning steps.
3. End with the final answer encapsulated in a LaTeX box.