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Verified 2026-08-14

Onboarding for AI features

First-run education: what the AI does, what it doesn’t, how to verify, and how to turn it off. HAX “initially” guidelines: make clear what the system can do and how well. PAIR has an entire pattern cluster on onboarding users to new AI f...

What it is

First-run education: what the AI does, what it doesn’t, how to verify, and how to turn it off. HAX “initially” guidelines: make clear what the system can do and how well. PAIR has an entire pattern cluster on onboarding users to new AI features and setting expectations.

<!-- IMAGE: first-run card: role, limits, verify habit, off switch -->

MEDIUM PRIORITYUI WIREFRAME
◷ IN PRODUCTION

Visual Spec & Architecture Diagram

Onboarding coachmarks overlay on a fake AI feature: what it can/can't do, privacy note, how to correct.

Educational Focus: First-run education reduces misuse.

Why it matters

Ambiguous onboarding creates overtrust and support tickets. PAIR case studies (e.g., Read Along) highlight expectation-setting and privacy transparency for sensitive audiences.

How it works (plain)

Show in under a minute:

  1. Role (draft vs decide)
  2. Limits / known failure modes
  3. Data uses & controls
  4. Good/bad output examples
  5. Verify habit + how to disable

Notify later when capabilities change (HAX G18).

Everyday example

A power tool’s safety sheet before the first cut—not a philosophy lecture mid-cut.

Try it

Write a 4-bullet first-run card for one AI feature. Time yourself reading it aloud; trim until under 30 seconds.

Myths

⚠️ Myth: Users will discover limits themselves safely.
✓ Reality: Many trust fluent output by default.
⚠️ Myth: One tutorial video replaces in-product cues.
✓ Reality: Just-in-time cues beat forgotten webinars.

Sources