Generative Artificial Intelligence (GenAI) systems have become integral to various sectors, facilitated through prompt engineering—a method allowing developers and end users to guide AI responses. Despite its prevalence, the concept of prompting suffers from inconsistent terminology and a nascent understanding. A recent paper by Sander Schulhoff and colleagues tackles this issue by providing a structured overview of the field. It introduces a systematic taxonomy, identifying 58 text-only prompting techniques and 40 methods across other modalities. Furthermore, it develops a comprehensive vocabulary of 33 terms specifically crafted to enhance clarity in discussing prompts. This framework not only unifies the language used across studies but also deepens the ontological understanding of prompts, facilitating more effective and nuanced interactions with GenAI systems. By synthesizing insights from a meta-analysis of existing literature, this work serves as a cornerstone for future developments in prompt engineering.