The Prompt Report: A Systematic Survey of Prompting Techniques
Authors: name: Sander Schulhoff, name: Michael Ilie, name: Nishant Balepur, name: Konstantine Kahadze, name: Amanda Liu, name: Chenglei Si, name: Yinheng Li, name: Aayush Gupta, name: HyoJung Han, name: Sevien Schulhoff, name: Pranav Sandeep Dulepet, name: Saurav Vidyadhara, name: Dayeon Ki, name: Sweta Agrawal, name: Chau Pham, name: Gerson Kroiz, name: Feileen Li, name: Hudson Tao, name: Ashay Srivastava, name: Hevander Da Costa, name: Saloni Gupta, name: Megan L. Rogers, name: Inna Goncearenco, name: Giuseppe Sarli, name: Igor Galynker, name: Denis Peskoff, name: Marine Carpuat, name: Jules White, name: Shyamal Anadkat, name: Alexander Hoyle, name: Philip Resnik

Generative Artificial Intelligence (GenAI) systems are being increasingly
deployed across all parts of industry and research settings. Developers and end
users interact with these systems through the use of prompting or prompt
engineering. While prompting is a widespread and highly researched concept,
there exists conflicting terminology and a poor ontological understanding of
what constitutes a prompt due to the area's nascency. This paper establishes a
structured understanding of prompts, by assembling a taxonomy of prompting
techniques and analyzing their use. We present a comprehensive vocabulary of 33
vocabulary terms, a taxonomy of 58 text-only prompting techniques, and 40
techniques for other modalities. We further present a meta-analysis of the
entire literature on natural language prefix-prompting.