This paper discusses PromptBreeder, a novel self-referential self-improvement mechanism for enhancing prompts in Large Language Models (LLMs). Unlike hand-crafted prompt-strategies, PromptBreeder evolves and adapts prompts for specific domains using LLM guidance. It mutates a population of task-prompts, evaluates them for fitness, and iterates over generations to evolve them. Remarkably, PromptBreeder also improves the mutation-prompts that enhance task-prompts, outperforming established prompt strategies on arithmetic and commonsense reasoning benchmarks. Additionally, it excels in evolving complex task-prompts for challenging tasks such as hate speech classification. https://arxiv.org/pdf/2309.16797.pdf