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The SMART Principles: Designing Interfaces That LLMs Understand

Jun 29, 2024 - medium.com
The article by Howard Zhou discusses the importance of interface design in Language Learning Models (LLMs) and introduces the SMART principles for developing Actions or Plugins for platforms like GPTs. The principles include keeping Simple Inputs, using Meaningful Strings, Avoiding Headers, adhering to the Single Responsibility Principle, and providing Transparent Descriptions. Zhou emphasizes that these principles help in designing interfaces that LLMs can easily comprehend, leading to the usability and success of the product.

The article also provides a step-by-step guide to building GPTs Actions using a structured engineering approach. This includes building a test set, designing the interface definition, implementing the interface, and following an iterative development process for adding new features. Zhou uses the example of Calendar EVA Now, an intelligent agent for managing schedules, to illustrate the process.

Key takeaways:

  • Designing interfaces that LLMs can easily comprehend directly impacts the usability and success of the product. The SMART principles are introduced to ensure clear, simple, and effective interfaces.
  • Each interface should have a single responsibility for maintaining clarity and simplicity in design. This principle, often referred to as the Single Responsibility Principle (SRP), simplifies debugging and maintenance.
  • Clear and concise descriptions are crucial for ensuring that LLMs can understand and execute commands accurately. Each interface and its parameters should be described in straightforward language, avoiding technical jargon or ambiguity.
  • To effectively build Actions for GPTs, a structured engineering approach is essential. This includes building a test set, designing the interface definition, implementing the interface, and iterative development when adding new features.
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