When to Use PromptWizard
✅ Best For
- Task-aware prompt refinement
- Creative domains and content generation
- Improving prompt style and meta-instructions
- Tasks requiring reasoning
❌ Not Ideal For
- Quick, simple optimizations
- When teacher model quality is low
- Projects with tight computational budgets
How It Works
PromptWizard uses a cycle of mutation, critique, and refinement:- Mutation: A teacher model generates prompt variations by mixing in different meta-prompts and styles (e.g., “Think step-by-step”).
- Critique: For prompts that perform poorly, the teacher generates detailed reasons for the failure.
- Refinement: The critiques are used to generate improved versions of the prompts.
- Selection: Beam search is used to evaluate all candidates and select the top performers for the next round.
1
Mutate
Generate creative variations of the prompt with different styles.
2
Critique
Analyze low-scoring prompts and generate failure critiques.
3
Refine
Use critiques to generate improved prompts.
4
Update Beam
Score all candidates and select the top N to continue.
Underlying Research
PromptWizard is based on the concept of self-evolving prompts, where an LLM iteratively improves its own instructions.- Core Paper: The framework is introduced in “PromptWizard: Task-Aware Prompt Optimization Framework” from Microsoft Research.
- Self-Evolution: The underlying mechanism is detailed in “Optimizing Prompts via Task-Aware, Feedback-Driven Self-Evolution”, which discusses the joint optimization of instructions and examples. The Microsoft Research Blog highlights this as a key direction for the future of prompt optimization.