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Hey 👋
This week: ship clearer onboarding and motion, avoid risky caret tweaks, harden UX maturity, and add measurable trust to AI features across teams.
- Adam at Unicorn Club 🦄
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🏗️ Build
Make better interfaces.
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A sharp teardown shows how to lead with value, show the experience, and bundle notifications so users reach the “aha” sooner.
Why it matters: Faster comprehension and earlier value moments lift activation and conversion without extra features.
Adopt this week: Replace a “how it works” first step with a value-first panel, add a 10–15s demo or real examples, and reframe notifications as “Don’t miss X” (one clear benefit).
Content check: Lead with why → show → ask; avoid duplicate permission prompts.
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When animations serve purpose, they aid speed and predictability, used on frequent or keyboard actions, they add drag and disconnect.
Why it matters: Perceived performance and responsiveness are UX outcomes. Motion misuse slows both.
Try this: Remove animation from high-frequency and keyboard-driven interactions. Cap UI motion under 300ms. Add initial tooltip delay but skip delays once open.
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New CSS caret-shape/color/animation features are tempting, but risk breaking focus visibility, non‑text contrast, and motion safety.
Why it matters: A flashy caret can fail WCAG, harm users, and reduce input clarity, especially in forms and editors.
Adopt this week: If experimenting (Chrome 140+), wrap caret animation in prefers-reduced-motion: no-preference , ensure strong contrast on all backgrounds, and keep blink ≤3/sec.
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🧩 Shape
Shared foundations across teams.
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NN/g outlines quiet signals of backsliding (checkbox rituals, unused metrics/systems, hero dependence) and lightweight ways to course‑correct.
Why it matters: Catching drift early prevents expensive rework, support spikes, and misaligned roadmaps.
Adopt this week: Schedule a 30–45‑minute quarterly maturity check‑in across strategy/culture/process/outcomes and start a visible “UX health log” to track wins and weak signals.
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AI raises expectations and complexity (agentic flows, unpredictability); core design still holds, but collaboration and clarity patterns must evolve.
Why it matters: Shared defaults for uncertainty, handoffs, and model behaviour avoid one‑off decisions and inconsistent UX.
First step: Draft a 1‑page AI UX playbook (when to show uncertainty/confidence, user control points, prototype fidelity) and agree a design–engineering working agreement for AI work.
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🚀 Ship
Release, measure, iterate.
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Trust is the invisible UI for AI; design and measure it with ability, benevolence, integrity, and predictability. Plus concrete telemetry and copy patterns.
Why it matters: Calibrated trust reduces over‑reliance and abandonment, improving safety and outcomes post‑release.
Adopt this week: Add trust instrumentation to one AI feature: log correction rate, and add two Likert items post‑task (“I understood why…”, “I’m confident in this output”); expose model uncertainty where useful.
Metric: Track correction rate + “understood why”/confidence (1–7) alongside change failure rates for the feature.
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Last week, we swapped stories of wins. Most loved were a creative solution and unexpected, positive feedback. Both got a nod from the community.
This week, I’m curious:
What’s the smallest interface fix or tweak you shipped (or spotted) that made things run just a bit smoother?
- 👌 Nailed a tiny copy update
- 🎨 Fixed a tricky visual detail
- ⏩ Untangled a flow or action
- 🤫 Noticed something clever in another product
Drop your triumph (or an emoji) in the community Slack.
Even the tiniest improvements deserve a mention.
Cast your vote or add a note—let’s give the subtle stuff its moment.
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Thanks for reading ❤️
Adam from Unicorn Club
Follow me on X or BlueSky
Connect on LinkedIn
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