Prompts First, Finally

TL;DR

This paper advocates for a 'Prompts First' approach in computer science education, emphasizing natural language as the ultimate abstraction level enabled by generative AI and large language models.

Contribution

It proposes shifting to a 'Prompts First' paradigm, aligning educational practices with the natural language capabilities of modern AI models.

Findings

Generative AI is transforming programming abstraction levels.

Natural language can serve as a universal problem-solving language.

A 'Prompts First' approach aligns education with AI's capabilities.

Abstract

Generative AI (GenAI) and large language models in particular, are disrupting Computer Science Education. They are proving increasingly capable at more and more challenges. Some educators argue that they pose a serious threat to computing education, and that we should ban their use in the classroom. While there are serious GenAI issues that remain unsolved, it may be useful in the present moment to step back and examine the overall trajectory of Computer Science writ large. Since the very beginning, our discipline has sought to increase the level of abstraction in each new representation. We have progressed from hardware dip switches, through special purpose languages and visual representations like flow charts, all the way now to ``natural language.'' With the advent of GenAI, students can finally change the abstraction level of a problem to the ``language'' they've been ``problem solving'' with all their lives. In this paper, we argue that our programming abstractions were always headed here -- to natural language. Now is the time to adopt a ``Prompts First'' approach to Computer Science Education.