The article outlines eight core user intents driving AI interactions, emphasizing the need for AI systems to recognize and adapt to these distinct modes. Each intent—Know/Learn, Create, Delegate, Oversee, Monitor, Find/Explore, Play, and Connect—dictates specific workflows, user interface designs, and success metrics. For example, the "Learn" intent focuses on helping users gain actionable insights quickly, with metrics like Comprehension Speed. The suggested workflow includes collecting context, running structured retrieval, and presenting information with clear sourcing to avoid overwhelming users. In the "Create" intent, the article highlights the importance of offering templates and controls for customization. It encourages designs that allow for iterative refinement rather than one-time perfection. Users should have the ability to edit specific parts while maintaining the rest of their work intact. The "Delegate" intent emphasizes the need for transparent workflows, where users can delegate tasks to AI without losing oversight. Success is measured by the reliability of task execution and the ability to manage multi-step workflows effectively. The article provides specific strategies for each intent. For instance, in the "Learn" intent, it advises structuring responses with a clear answer first, followed by supporting details, and ensuring sources are easily accessible. For "Create," it suggests providing initial drafts and ensuring changes can be reversed. In "Delegate," the focus is on deterministic workflows with progress tracking and audit logs, ensuring users understand what the AI is doing and can confirm actions before they occur. Each intent is designed to minimize cognitive load, maintain user control, and enhance the overall interaction experience with AI systems.