The Smart Principles: Designing Interfaces That LLMs Understand
Designing user interfaces for Large Language Models (LLMs) is crucial for application success. SMART principles like Simple Inputs, Meaningful Strings, and Transparent Descriptions enhance clarity and reliability. Implementing these principles improves user experience and functionality.
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The article discusses the importance of designing interfaces that Large Language Models (LLMs) can understand to ensure the success and usability of applications. It introduces the SMART principles, focusing on Simple Inputs, Meaningful Strings, Avoiding Headers, Responsibility, and Transparent Descriptions. By simplifying input parameters, using clear strings instead of numeric values, handling authorization correctly, maintaining single responsibilities, and providing transparent descriptions, interfaces become more user-friendly for LLMs. The article emphasizes the significance of these principles in enhancing the clarity, interpretability, and reliability of data for LLMs, particularly on platforms like GPTs. It also outlines an engineering approach for building GPTs Actions, using Calendar EVA Now as an example, to systematically design and implement interfaces that align with LLM capabilities. By following structured steps, developers can create efficient and user-friendly Actions for GPTs, improving overall user experience and application functionality.
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