The clarification flow in Deep Research allows the model to ask users for more information, enhancing the interaction and improving the accuracy of the responses. To get the best response from the research model, the prompt needs to be well-specified and detailed, as users typically don't provide all necessary information in the first prompt.

Deep Research is particularly effective for detailed queries that require extensive reading and understanding of web content to provide accurate answers.

Deep Research was developed to tackle tasks requiring extensive online research and reasoning, enabling users to efficiently gather information and make informed decisions across various domains.

Deep Research has been surprisingly popular for coding tasks, helping users with code searches, documentation, and script writing, which was not initially anticipated as a primary use case. It also excels at synthesizing information and finding specific, hard-to-locate facts on the internet, especially when given detailed descriptions of what users want.

To accurately understand your users, ask open-ended questions during interviews. This approach helps uncover their stories and emotions, which often reveal the most pressing problems to solve.

Our user research involves asking behavioral questions rather than validating specific features, which helps us understand user needs better.

Deep Research allows users to generate comprehensive reports on topics of interest, significantly enhancing their learning experience.

Deep research starts its analysis by gathering available resources and collecting information as it goes.

Asking specific questions about how potential customers currently handle a problem can reveal valuable insights into their needs and challenges, and understanding user motivation is critical for solving their problems effectively.