UX Collective · 2 Jun 2026The most important part of building your taste is to hand it offThe article argues that design taste trapped in individual contributors' heads creates a bottleneck — teams can't scale quality output unless the person with taste has built systems, principles, and critique frameworks that others can use autonomously. The cost of hoarded taste is slow review cycles, inconsistent execution, and designers who cannot grow.
For a product team scaling AI-generated UI or operating with a lean design org, externalising taste into documented principles and review rubrics is the only way to maintain quality as output volume increases.
The piece examines how default settings in digital products encode decisions made by designers or business stakeholders — not users — and how those defaults shape behaviour at scale without users consciously choosing them. It challenges teams to treat every default as a deliberate design decision with measurable downstream effects.
In a travel booking funnel, defaults around fare class, flexibility, ancillary pre-selection, and payment method selection carry real revenue and conversion implications — treating them as neutral is a design accountability gap.
The article applies Sturgeon's Law (90% of everything is mediocre) to AI-generated content, arguing that increased content volume from AI tools amplifies the mediocrity problem rather than solving it — more output means more noise, not more quality, unless curation and quality standards are built into the generation process.
Travel platforms using AI to generate itinerary copy, hotel descriptions, or destination content at scale will flood their product with generic, low-trust content unless they build editorial standards into the generation pipeline.
The piece argues that static screenshot-based inspiration archives teach designers to copy visual outcomes rather than understand motion, micro-interaction, and taste formation — the author identifies four motion-focused archives that capture the reasoning layer beneath visual polish. The core argument is that AI can replicate static aesthetics but cannot yet transfer the kinetic and temporal sensibility of strong interaction design.
For a travel product team shipping interactive search, date pickers, map surfaces, and booking flows, motion and micro-interaction quality is a trust and comprehension signal — not decoration — and teams without exposure to it will produce flat, unconvincing interactions.
Gergely Orosz documents that developers using AI coding agents are generating twice as much code as six months ago — but code volume is outpacing review capacity, introducing quality, reliability, and tech debt problems that compound faster than teams can address. The rational fix proposed is deliberate upfront planning and specification before invoking AI generation, not more generation speed.
Product and engineering leads who are measuring AI-assisted development by velocity or output volume without a corresponding quality gate are accumulating invisible tech debt that will slow iteration speed in proportion to how much was rushed.
