# Automatic Prompt Engineer

> Automatic Prompt Engineer (APE) uses a language model to generate candidate instructions for a task from input-output examples, scores each candidate on held-out data, and selects the best one.

- Identifier: PTL-0073
- Category: Prompt Optimization
- Canonical URL: https://protologue.com/t/automatic-prompt-engineer/
- Also known as: APE
- Introduced: 2022

## Description

APE discovered a zero-shot chain-of-thought trigger that outperformed "Let's think step by step" on some benchmarks, and framed prompt writing as a search problem that models can solve themselves.

## Related terms

- [Prompt Engineering](https://protologue.com/t/prompt-engineering/)
- [Optimization by Prompting](https://protologue.com/t/opro/)
- [DSPy](https://protologue.com/t/dspy/)
- [Meta-Prompting](https://protologue.com/t/meta-prompting/)

## Sources

- Zhou et al. (2022). Large Language Models Are Human-Level Prompt Engineers. https://arxiv.org/abs/2211.01910

## Cite this entry

Protologue. (2026). Automatic Prompt Engineer. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0073). https://protologue.com/t/automatic-prompt-engineer/

License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)