AI & Design Blog
Loading…
Loading…
Page 3 of 8
Every AI product ships with the same blinking cursor and blank text box. It's time designers stopped accepting the chat prompt as the default — and started inventing interaction models that actually fit how people work.
AI tools promise designers unprecedented autonomy — fewer gatekeepers, more agency. But what happens when those 'bottlenecks' were actually the guardrails catching your blind spots?
The EU's new AI labelling guidelines create an awkward design problem: how do you prominently disclose something your users never asked for in the first place?
YouTube penalised Kurzgesagt's handcrafted animation as AI-generated slop. When audiences and algorithms can't tell craft from AI, your design process becomes your most valuable proof.
The tech industry keeps shipping AI features nobody asked for. The real design challenge isn't building with AI — it's knowing when not to.
AI tools let you build a prototype in a weekend. But speed without validation is just the fastest route to the wrong product. The real design skill now isn't building — it's knowing what's worth building.
The design community is converging on an uncomfortable truth: most people don't want more AI features. They want the right ones, in the right places, delivered in ways they'll never notice.
AI deals in probabilities, but most interfaces present its outputs as certainties. It's time designers learned to communicate confidence — not just content.
AI tools are only as good as the design systems they read. If your tokens are messy and your docs are vague, no model can save you — it's time to design for your system's newest, least forgiving user.
AI tools deliver confident-sounding recommendations, but confidence isn't certainty. Probabilistic design — and tools like CSS's contrast-color() — show us how to build systems that embrace uncertainty instead of hiding it.