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The UX of AI Features: Designing for Probabilistic Software

AI features are sometimes wrong by design — the UX job is setting expectations, showing sources, making review effortless, and keeping the user in control of consequential actions.

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[ SET EXPECTATIONS AT · 01 ]

Label AI-generated content, communicate confidence honestly, and scope the promise ('drafts for your review') — overclaiming is how one visible error destroys feature trust.

[ REVIEWABILITY AS THE · 02 ]

Reviewability as the core interaction

Citations and sources one click away, diffs for AI edits, and accept/modify/reject as first-class verbs — the review loop is the feature.

[ GRACEFUL UNCERTAINTY · 03 ]

Graceful uncertainty

Designed 'I don't know' states with fallbacks, escalation paths, and never fabricated confidence — the refusal path is a UX deliverable, not an error condition.

[ FEEDBACK THAT IMPROVES · 04 ]

Feedback that improves the system

Thumbs, corrections, and edit capture wired to the evaluation loop — users become the quality flywheel when the UI makes contributing effortless.

Skipping the discipline this article describes until an incident, audit, or stalled project forces it — every practice above is cheaper adopted early than retrofitted under pressure.

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