- Alex Fiannaca
- Carrie Cai
- Chinmay Kulkarni
- Michael Terry
Existing tools for prompt programming provide little support to prompt programmers. Consequently, as prompts become more complex, they can be hard to read, understand, and edit. In this work, we draw on modern integrated development environments for traditional programming to improve the editor experience of prompt programming. We describe methods for understanding the semantically meaningful structure of natural language prompts in the absence of a rigid formal grammars, and demonstrate a range of editor features that can leverage this information to assist prompt programmers. Finally, we relate initial feedback from design probe explorations with a set of domain experts and provide insights to help guide the development of future prompt editors.
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