ai-onboarding--calibrationlisted

# AI Onboarding & Calibration Design first-time and ongoing experiences that help users understand what AI can and cannot do, build accurate expectations, and discover capabilities at the right pace. The CALIBRATE framework treats onboarding as a continuous calibration process, not a one-time tutorial. ## Core Principle AI onboarding is fundamentally different from traditional software onboarding. In traditional software, features are deterministic - a button always does the same thing. In AI products, the same input can produce different outputs, capabilities have fuzzy boundaries, and what the AI "can do" depends on context. **You are not teaching features. You are calibrating a mental model.** --- ## The CALIBRATE Framework | Letter | Principle | Design Question | |---|---|---| | **C** | Communicate Boundaries | Does the user know what the AI is and isn't good at? | | **A** | Anchor with Examples | Have you shown, not told, what the AI can do? | | **L** | Layer Complexity | Do simple use cases come first, with advanced capabilities revealed over time? | | **I** | Invite Experimentation | Is there a safe, low-stakes way to explore what the AI can do? | | **B** | Build Incrementally | Does the user's understanding deepen with each interaction? | | **R** | Recalibrate After Failures | When the AI disappoints, does the onboarding help users adjust expectations? | | **A** | Adapt to Expertise | Does the experience change based on the user's skill level? | | **T** | Track