– Large language models (LLMs) can follow natural-language-like instructions.
– Prompt programming allows users to express programming intent in plain language.
– Existing prompt editing interfaces provide basic text editing interactions.
– Prompt programming lacks a predefined grammar, making it difficult to support.
– This paper explores the challenges and opportunities of creating a dedicated LLM prompt editor.
– The paper introduces techniques for understanding and inferring the semantic structure of prompts.
– The paper presents insights from pilot tests and discusses design challenges and opportunities.
– The research identifies a new challenge in programming tool design: supporting prompt programming without a well-defined programming language.
– Solo Performance Prompting (SPP) enhances problem-solving abilities in complex tasks.
– SPP reduces factual hallucination and maintains strong reasoning capabilities.
– Cognitive synergy emerges in GPT-4 but not in less capable models.
– Existing tools for prompt programming lack support for prompt programmers.
– The paper explores methods for extracting the structure of natural language prompts.
– The paper presents insights and challenges in designing a prompt editor.
– Findd challenges and opportunities for supporting prompt programmers.
– Developed prompt editor features based on the semantic structure of prompts.
– Conducted initial pilot testing and presented key insights.
– Prompt programming lacks a predefined grammar but has inherent semantic structure.
– Described open questions, design challenges, and opportunities for future support.
– Methods for extracting the structure of natural language prompts.
– Range of editor features to assist prompt programmers.
– Initial feedback from design probe explorations with domain experts.
– Solo Performance Prompting (SPP) helps a computer program think like different people.
– It uses different personas to solve problems and get accurate knowledge.
– SPP reduces mistakes and makes better plans compared to other methods.
– It works well in tasks like writing stories and solving puzzles.
– SPP is better in GPT-4 model compared to other models.
