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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.
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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?
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A definitive breakdown of tricky CSS sticky failures: scroll containers, bounding context bugs, and flex/grid gotchas. Plus fixes with practical Tailwind/JSX examples.
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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.
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🧩 Shape
Shared foundations across teams.
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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?
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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.
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🚀 Ship
Release, measure, iterate.
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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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Get our "7 Positioning Sins That Cost B2B Brands Millions" guide when you join. It's free, join 10,000+ B2B executives.
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One AI workspace where the whole team is part of the creative process, customer research finally informs product strategy, and concepts come to life at lightning speed.
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🎲 Also worth a look
A few extras we've found.
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How giving LLMs persistent context (via code and file structure) turns them from generic interns into truly high-leverage partners for product teams.
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Other ways I can help...
Here’s how I can help you tackle your next challenge:
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🎯 1:1 Mentorship – Personalised advice on portfolios, career moves, or challenges you're facing.
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💡 Hire Me – Let’s work together to launch your vision, get expert guidance and make an impact.
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Thanks for reading ❤️
Adam from Unicorn Club
Follow me on X or BlueSky
Connect on LinkedIn
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