UX Collective: Designing for the proxy — why AI is changing who reads first
What the article is about
Aurélie Radom’s August 2026 piece on UX Collective raises a question that has quietly become central to every design decision: before a human user encounters your interface or documentation, an AI system has already read, summarized, and interpreted it. Radom calls this intermediary role the “proxy” — and argues that its existence changes the design problem in ways most practitioners have not yet acknowledged.
The article is not a guide to building AI products. It is a reflection on how generative AI has restructured the chain between creation and consumption. When a language model reads a help page and produces a summary for a user, the original design — its hierarchy, its personality, its careful wording — may never reach the person it was written for. What reaches them is the model’s interpretation.
Who it is for
The article is most useful for UX writers, content designers, and product designers who are starting to notice that optimizing for search engines no longer captures the full picture. It is also relevant for anyone responsible for documentation, onboarding copy, or any text-heavy interface that surfaces inside AI-assisted tools.
Key arguments
Radom draws on historical precedent — the way social platforms once incentivized emotional engagement over meaningful connection — to caution against letting machine interpretability become the primary design objective. She argues that designing for the proxy risks hollowing out the human qualities of an interface: personality, warmth, and the kind of contextual judgment that makes content trustworthy.
Her practical frame is about balance rather than resistance. Machines benefit from structure, clear labeling, and predictable patterns. Humans respond to voice, emotion, and earned trust. A design that works for both does not sacrifice one for the other; it finds places where structure and personality can coexist.
She also makes a point about invisible work. When AI generation makes visual output cheap and abundant, what becomes scarce is the underlying system: the accessibility logic, the information architecture, the component behavior under edge conditions. These are exactly the things a screenshot cannot reveal, and exactly the things a proxy model cannot reconstruct from text alone.
What it does not cover
The article is more analytical than prescriptive. It does not offer a methodology for auditing existing designs against proxy readability, nor does it address technical approaches to structured data markup or schema that would make content more parseable by AI systems. Designers looking for concrete implementation steps will need to look elsewhere.
Who it is useful for
Designers and content strategists who feel the design problem has shifted but cannot quite articulate why will find this article useful as a frame for that intuition. It is worth reading before a content audit or any project where documentation is part of the deliverable.