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🦄 Are Your UIs Too Flat for 2026?

November 12, 2025

Hey 👋

AI is changing product research, prototyping, and the mechanics of interface clarity, plus why putting insight into action is key to team impact.

have a great week, catch you on the next one - Adam at Unicorn Club 🦄

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🏗️ Build

Make better interfaces.

Material 3 Expressive: Building on the failures of flat design

Google’s Material 3 Expressive reverses a decade of flat design, restoring visual signifiers, containment, colour, and clear boundaries, to aid recognition and scanning.

Why it matters: Data-driven research shows significant gains in speed and confidence for all age groups, closing gaps and reducing click uncertainty.
Adopt this week: Audit key UI elements. Are your affordances (like buttons, containers) visually strong enough? or are you falling into the “too clean, too flat” trap?

The Weird Parts of position: sticky;

A definitive breakdown of tricky CSS sticky failures: scroll containers, bounding context bugs, and flex/grid gotchas. Plus fixes with practical Tailwind/JSX examples.

Why it matters: Sticky UI fragments still trip up teams and create inconsistent layouts or scroll bugs, especially in complex grid/flex contexts.

Experiment like never before

AI-powered prototyping (with Figma Make, etc) slashes the cost and turnaround on rapid and research-through-design experiments, unlocking more room for testing wild ideas and validating edge-case flows.

Why it matters: Faster, higher-fidelity prototyping collapses research-to-decision cycles and enables more focused, evidence-rich iteration on real interactions.

🧩 Shape

Shared foundations across teams.

From design to direction: Bridging product design and AI thinking

Drawing analogy between design iteration (friction) and AI training (loss), this piece reframes product velocity as a multi-layer system optimised through feedback, signals and intent. From UI to business impact.

Why it matters: Reframing design through optimisation links design, telemetry, and metrics, encouraging cross-team instrumentation habits and measurement mindsets.
First step: Map a recent product change through “friction-to-signal”. What was measured, where did feedback/intent break down, and can your team see this at every layer?

How to land a UX job in 2026

Reflecting on team evolution in an AI-shaped world: mapping value, embracing AI-powered research, deepening business collaboration, and refocusing on holistic/system-level skills.

Why it matters: Teams that ground design in business context, behavioural research, and emerging prototyping tech will shape both product direction and their own long-term value.

🚀 Ship

Release, measure, iterate.

Insights Aren’t Outcomes: Research Recommendation Breakage

Most research work fails to yield outcomes due to “breakage”. Somewhere between a well-crafted insight and an actual shipped fix, the value leaks away. NN/g calls for structured tracking of recommendation adoption, not just reporting.

Why it matters: Teams unlock compounding benefits (and protect researcher morale) by tracking whether findings are actioned and closing the loop on intended impact.
Adopt this week: Pick one recent research output, trace each insight to an outcome in your backlog or shipped product. Where did breakage happen: documentation, ownership, delivery?

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