Chat to Explore Contents is a revolutionary new pattern that is changing the way users search for information and get answers. This pattern allows users to conduct an initial search and then refine it using a chat model. This approach is more intuitive and personalized, as it narrows the scope of interaction with the chat model by providing context from the initial search.

Users can get the information they need more quickly and accurately, without having to sift through irrelevant search results. Search giants like Google and Bing have already adopted this pattern, using their search engines to contextualize the chat models. By adopting Chat to Explore Contents, you can offer your users a more efficient and personalized search experience that keeps them engaged and coming back for more.

Is a powerful new pattern that addresses the challenge of users viewing an entity, document, or spreadsheet on a page or application and having questions about what they see.

By implementing this pattern, you can empower your users to ask questions and receive immediate and relevant answers in a way that is familiar and natural to them. This approach can increase user engagement, improve understanding, and ultimately lead to a more positive user experience. With Chat to Analyze, you can create a more conversational and personalized interface that caters to the needs of your users.

Intent-Based UI Navigation is an innovative pattern that helps users achieve their goals more efficiently. Often, users enter a system with a specific task in mind, which can result in complex navigation as systems offer more features. With Intent-Based UI Navigation, users can accomplish their tasks using natural language, which leads to a more intuitive and user-friendly experience.

This pattern utilizes LLMs (Language and Learning Models) for progressive discovery based on user intentions. By combining the productivity of direct manipulation interfaces with conversational ones, users can navigate the system with ease. In certain contexts, the navigation becomes hybrid, allowing users to discover new parts of the system using natural language and guiding them to the most productive areas.

Generating and editing content can be a time-consuming process, requiring significant effort to summarize, edit, and format. However, with the emergence of AI-powered models, there is a new solution to this problem. These models can complete, summarize, format, and even compare content across various interfaces, going beyond simple autocomplete features found in programming environments.

In designing user interfaces, it is important to consider whether it is necessary for users to fill or write something. If so, we must explore the use of the Magic Auto-Complete pattern, which can reduce the time and effort required to create and edit content, while also improving the overall quality and accuracy of the output.