The launch of Shopify’s Spring Editions 2026 continued their focus on the agentic infrastructure, with a GA release of their Universal Commerce Protocol (UCP) co-developed with Google and a GA for Shopify’s Global Catalog MCP, among others. What we’ve learned from working with the Early Access releases, on behalf of our clients, is that the catalog alone is not enough to show up properly in LLMs. Brands who are highly protective of their identity (which is basically any brand worth their stuff) demand to show up with much more specificity about who their products are for, which features are important, key ingredients, sustainability claims, etc. All of which is content that doesn’t live in the Product Catalog.
That means that the most important next step for brands is not looking outward to AI adoption, but looking inward at how they're managing their brand with a richer and broader approach. This requires brands to be much more intentional about content, which some brands may have treated as perfunctory, nice-to-have filler. Brands are also forced to relook at how customers are talking about them, from Customer Reviews, to Reddit and other sources of customer feedback.
LLMs are making decisions about which products to show, which brands to recommend, which attributes matter, and which alternatives deserve consideration. Unlike Google Search, brands cannot pay their way into showing up in these conversations. The inputs that shape visibility are increasingly the same inputs that shape understanding.
Design Systems for intelligence
For years, brands have invested heavily in controlling how they show up. One core deliverable in the ecommerce industry has been the Design System, which governs typography, layout, color, photography, and sometimes tone-and-voice guidelines. We apply design systems to create marketing assets, website pages, mobile apps, emails, etc. While all of that work still matters, in an AI-mediated world, it is no longer sufficient to only define what the customer sees directly.
The new role of brand, in it’s effort to control representation, is to power the intelligence, memory, discovery, experience, and infrastructure that shape how customers make decisions, both on and off the site.
To do this successfully, brands need to build brand assets that intelligence systems understand. That means shifting from human-facing documentation (like Figma) into intelligence-readable documentation as the core source of truth. At Domaine, we’ve shifted to expanding and enriching our deliverables by also creating Design markdown files with content that hasn’t lived in Design Systems previously. This means that the design process internally and with our clients has a deeper recognition of how markdown files operate in the larger context of brand discoverability.
The product catalog as a new “brand bible”
Winning brands will be the ones with the the strongest underlying intelligence layer: structured product data, authoritative content, clean architecture, connected customer memory, and commerce systems that give the brand control over how information is stored, interpreted, and activated.
For many organizations, the product catalog is still viewed as an operational asset. It is something to manage, enrich, sync, and maintain. But in the agentic era, the catalog becomes much more strategic, it becomes the source material that AI systems use to understand the brand.
Today, a product description is no longer that rarely-read copy on a Product Detail Page, and a product attribute is no longer just a merchandising field. These are now rich content assets that have an impact to how a brand shows up in LLMs. Reviews, materials, sizing, use cases, ingredients, compatibility, sustainability claims, care instructions, FAQs, and editorial content all become part of the intelligence layer that determines whether a brand can be accurately represented by AI. In other terms, the enriched product catalog becomes a core brand asset.
The product catalog now tells external systems what the brand is, what it offers, who it is for, and why it should be recommended.
If that catalog is thin, fragmented, inconsistent, or incomplete, the brand will be underrepresented. If it is rich, structured, and strategically built, the brand gives every AI system more context to reason from.
What the new role of brand looks like
As agents become more capable, the question for brands then shifts from “How do we ensure we show up in LLMs?” to “How do we make sure ALL the systems making decisions on behalf of customers have the right understanding of who we are as a brand?”
At Domaine, this is how we are increasingly thinking about the next phase of commerce strategy. The work is about helping brands build the foundations that allow intelligence to operate in their interest.
That means:
- Treating catalog architecture as a strategic brand asset
- Connecting CRM, content, commerce, and customer data so they reinforce one another rather than operating as separate systems
- Designing customer experiences where intelligence feels natural, useful, and aligned to the brand (and in almost every case the AI should feel invisible).
- Helping brands understand where AI-powered discovery is creating new opportunities for acquisition, and where poor data quality or fragmented content may be limiting visibility.
For brands, AI shouldn't be treated as a feature layer. The commerce stack itself is becoming more intelligent, which makes the quality of the underlying foundation has become more important than ever.
A framework for brand in the age of AI
To put it another way, the primacy of brand is built across five interconnected areas:
- Intelligence: the deep brand knowledge systems that defines who the brand is, how it speaks, what it knows, where it’s differentiated.
- Memory: the customer context a brand learns and grows over time.
- Discovery: how the brand is found, evaluated, and recommended across AI-powered experiences.
- Experience: how intelligence is expressed in ways that feel useful, intentional, and original.
- Control: the infrastructure, data, and direct relationships that keep the brand from becoming dependent on intermediaries to represent it.
None of these areas are new or live in isolation, but in the age of AI they have a new degree of interdependency. Together, they determine how well a brand can participate in an AI-driven commerce environment without losing control of its own narrative, customer relationships, or commercial future.
Having spent my first 20 years in ecommerce on the brand-side, I’m naturally predisposed to place Brand in a new powerful and central role in AI commerce. While we know that AI will continue to change how customers discover, evaluate, and buy from brands, it’s important to go one level deeper in defining what a brand is. It goes deeper than logo, photography, color and typefaces - so our deliverables have changed accordingly. Ultimately, the goal is to ensure that the intelligence layer representing your brand, both in discovery and throughout the customer experience, is one that has been intentionally designed and built.
If you're evaluating how AI will impact your customer experience, content strategy, product catalog, or commerce ecosystem, reach out to our team.
