In a new article for Forbes Agency Council, ArtVersion Principal and Creative Director Goran Paun examines how large language models (LLMs) are reshaping the way brand narratives are interpreted, surfaced, and repeated — and why design now plays a decisive role in whether those stories are understood accurately.
The article argues that a fundamental shift has already occurred. Brand storytelling is no longer interpreted solely by human audiences. LLMs increasingly sit between organizations and the people trying to understand them, summarizing capabilities, recommending partners, and contextualizing expertise. These systems do not read websites sequentially. They infer meaning from structure, consistency, and the relationships between concepts.
Paun’s central premise is not that brands should write for machines, but that they must design narratives that can be interpreted without distortion. When services, positioning, and philosophy blur together, or when terminology shifts across pages, models compensate by filling gaps probabilistically. That is where misrepresentation begins.
The article distinguishes clarity from simplification. Many organizations respond to this shift by flattening their messaging or leaning on generic claims. According to Paun, this approach undermines comprehension. LLMs rely on precision, not vagueness. Stable language, clearly defined roles, consistent descriptions of who a company serves, and explicit explanations of how work is differentiated allow models to form accurate representations over time.
A key focus of the piece is narrative structure. While traditional storytelling prioritizes persuasion and emotional arc, LLMs also require structural logic. Identity must precede promotion. Capabilities must be explained before they are marketed. Context must come before claims. This mirrors principles long established in user experience and web design, where hierarchy and sequence determine whether meaning is legible.
Paun extends this logic to design systems, reframing them as narrative systems rather than purely visual frameworks. Consistent hierarchy, repeatable page structures, and predictable content roles reduce ambiguity at scale. When every service or case study follows a coherent conceptual pattern, interpretation becomes more reliable — for both humans and machines.
The article also addresses metadata and structured data, positioning them as narrative signals rather than technical afterthoughts. Schema and metadata communicate entity type, relationships, and intent. When they reinforce on-page content, confidence increases. When they contradict it, models lose certainty, often resulting in oversimplified or inaccurate summaries.
Rather than framing the issue as one of rankings or visibility, the article emphasizes accuracy. As LLMs increasingly act as intermediaries, they are effectively retelling brand stories. If those stories are not designed to be understood, authorship is lost.
Paun concludes by identifying a broader transition underway: from persuasion-first digital storytelling to comprehension-first design. If systems cannot understand an organization, they cannot represent it accurately. The brands most likely to remain relevant are those whose narratives are structurally sound, conceptually consistent, and deliberately designed across every layer of their web presence.