Prompting as Scientific Inquiry
Abstract
Prompting is the primary method by which we study and control large language models. It is also one of the most powerful: nearly every major capability attributed to LLMs—few-shot learning, chain-of-thought, constitutional AI—was first unlocked through prompting. Yet prompting is rarely treated as science and is frequently frowned upon as alchemy. We argue that this is a category error. If we treat LLMs as a new kind of organism—complex, opaque, and trained rather than programmed—then prompting is not a workaround. It is behavioral science. Mechanistic interpretability peers into the neural substrate, prompting probes the model in its native interface: language. We argue that prompting is not inferior, but rather a key component in the science of LLMs.
BibTeX
@inproceedings{
holtzman2025prompting,
title={Prompting as Scientific Inquiry},
author={Ari Holtzman and Chenhao Tan},
booktitle={The Thirty-Ninth Annual Conference on Neural Information Processing Systems Position Paper Track},
year={2025},
url={https://openreview.net/forum?id=yZU8kdwafM}
}