Intent-to-Interface: Adaptive AI Workspace An interface that reshapes itself around the user’s current goal THE PROBLEM Modern applications make users navigate fixed dashboards, menus, filters, and workflows—even when their goals differ. Finding the right information can take more effort than completing the task itself. THE CHALLENGE Build an AI-powered adaptive workspace that understands a user’s current intent and dynamically arranges the interface around the task they are trying to accomplish. EXAMPLE: PREPARE FOR A CLIENT MEETING The user says: “I need to prepare tomorrow’s client meeting.” The workspace could bring together a client overview, recent communication, open issues, product usage, the previous meeting, suggested talking points, and relevant actions. EXPECTED CAPABILITIES • Understand user intent and clarify ambiguity when needed • Select relevant information and tools • Dynamically arrange UI components for the task • Generate task-specific interfaces while preserving a consistent design system • Adapt as the user’s goal changes • Explain why particular information and actions were surfaced DEMO REQUIREMENT Start with a generic dashboard. Give the system three different tasks—for example, prepare for a client meeting, investigate a drop in product usage, and review overdue project work. Show the interface reorganising itself for each task. DESIGN EXPECTATIONS The result should remain usable, coherent, and accessible. It should not simply generate a page of text: it should select and arrange interface components that actually support the task. WHAT A STRONG SOLUTION SHOWS Accurate intent detection, useful component selection, smooth adaptation, consistent visual design, and understandable explanations for interface changes. CORE CHALLENGE Build an interface that adapts to the user’s goal instead of forcing the user to adapt to the interface