"Progressive disclosure is a well-known principle in UX design. This principle is about showing users only what they need right now, and revealing more options or information gradually as they interact or gain context. The goal is to reduce cognitive load, keep interfaces clean and approachable, and still support advanced use cases when needed. The principle of progressive disclosure can be applied not only to the user interfaces we design, but also AI tools we use."
"The reason for using the principle is pretty much the same as for UX design: to keep context clean and relevant to the task at hand. And by ' context ' I mean the context window that the AI tool uses when it processes your task. Context window is the maximum amount of information an AI model can "see", remember, and reason over at one time, including your prompt, instructions, conversation history, and any pasted documents."
Progressive disclosure limits visible information to what is needed at the moment and reveals more options or details as context grows. Applying progressive disclosure to AI tools manages the model's context window, preserving relevant content and reducing irrelevant noise. The context window contains prompts, instructions, conversation history, and pasted documents and constrains what the model can see, remember, and reason about at once. Using progressive disclosure for AI reduces cognitive load, keeps interactions focused and approachable, and enables advanced use cases by revealing additional information only when necessary.
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