Agentic commerce’s dirty little secret.
It seems like every other conversation on LinkedIn these days revolves around agentic commerce, right?

And every one of these in one way or another expresses an urgency to get merchants ready: adopt the protocols, publish the feeds, make your catalog legible to ChatGPT and Gemini and the rest. All of it is real and necessary. But almost no one is asking the uncomfortable question underneath it.
When discovery moves from the storefront to the agent, who actually wins? Because by default, it’s not the merchant.
๐ช๐ต๐ผ ๐ฎ๐ด๐ฒ๐ป๐๐ถ๐ฐ ๐ฐ๐ผ๐บ๐บ๐ฒ๐ฟ๐ฐ๐ฒ ๐ฟ๐ฒ๐ฎ๐น๐น๐ ๐ฏ๐ฒ๐ป๐ฒ๐ณ๐ถ๐๐
Pretty sure the ACP (Agentic Commerce Police) are going to be knocking on my door after this one.
Follow a single agentic purchase. The shopper no longer starts on a brand’s site. They start with an AI assistant, describe what they want, and let it find, compare, and increasingly transact on their behalf. Two parties are structurally advantaged by that shift. The first is the AI platform, which now owns the top of the funnel, the shopper relationship, and the ad and placement economics forming on top of it. The second is the large marketplace, which gives the agent exactly what it wants: an enormous, uniformly structured, always-available catalog it can trust and pull from in one call. Scale and structure are what an agent rewards, and marketplaces are built out of both. This is an inevitable and completely logical migration for marketplaces, commerce platforms and providers.
However, an individual merchant enters that system as one source among millions. Even fully agentified, armed with every protocol and a clean outbound feed, a single store is a needle competing against a haystack with billions of products for a slot in an answer whose ranking logic it does not control and cannot see.
๐ง๐ต๐ฒ ๐ป๐ฒ๐ฒ๐ฑ๐น๐ฒ ๐ถ๐ป ๐ฎ ๐ฏ๐ถ๐น๐น๐ถ๐ผ๐ป-๐ฝ๐ฟ๐ผ๐ฑ๐๐ฐ๐ ๐ต๐ฎ๐๐๐๐ฎ๐ฐ๐ธ
Picture the actual query. Someone asks ChatGPT for “a nice, knee-length, belted, lightweight trench coat for summer business wear in Seattle.” That is a rich, specific, high-intent request, exactly the kind agents are good at. Perfect. So what happens next? The agent scans a massive pool (millions) of candidate products and ranks them by relevance, structured-attribute match, availability, authority, price, and whatever commercial arrangements sit in the background, then returns a short list. How many of those candidates are individual DTC catalogs, and how many are marketplace listings?
For a store like Cassie’s Kurations to surface in that answer, its data has to be not just clean but better-matched than everything else in the pool, and the ranking still has to choose to show that result instead of a marketplace row selling something close enough. The odds are not zero. They are also not something to build a business on.
That is the part no one says out loud. Agent-side discovery is a lottery whose house is the platform and whose most reliable winners are the aggregators, who always get a cut of each transaction.
๐๐ฒ๐ถ๐ป๐ด ๐ฎ๐ด๐ฒ๐ป๐-๐ฟ๐ฒ๐ฎ๐ฑ๐ ๐ถ๐ ๐ป๐ฒ๐ฐ๐ฒ๐๐๐ฎ๐ฟ๐, ๐ป๐ผ๐ ๐๐๐ณ๐ณ๐ถ๐ฐ๐ถ๐ฒ๐ป๐
None of this is an argument against agentic commerce. Every merchant should have clean, enriched product data and universal agentic feeds. If your catalog is not legible to agents, you are not in the lottery at all, and staying out is not a strategy. Legibility is table stakes.
But letโs at least be honest about what that ticket buys. It gives the merchant a chance to be surfaced by someone else’s algorithm, into someone else’s interface, often as a listing inside someone else’s marketplace, with someone else’s take rate attached. Play only that game and you have volunteered to have your discovery bled off the top and handed downstream, to the platforms first and to you second, if you are lucky. The brand you built becomes a drop ship supplier.
๐ฃ๐ฟ๐ผ๐๐ฒ๐ฐ๐ ๐๐ต๐ฒ ๐ฐ๐ฎ๐๐๐น๐ฒ ๐๐ผ๐ ๐ฏ๐๐ถ๐น๐
The counter-move is not to opt out of agents. It is to run a multi-pronged discovery plan and keep as much discovery as possible, on ground you own. ๐ง๐ต๐ฒ๐ฟ๐ฒ ๐ถ๐ ๐ฒ๐ ๐ฎ๐ฐ๐๐น๐ ๐ผ๐ป๐ฒ ๐ฝ๐น๐ฎ๐ฐ๐ฒ ๐๐ต๐ฒ๐ฟ๐ฒ ๐๐ต๐ฒ ๐ฎ๐ป๐๐๐ฒ๐ฟ ๐๐ผ ๐ฎ ๐๐ต๐ผ๐ฝ๐ฝ๐ฒ๐ฟ’๐ ๐พ๐๐ฒ๐ฟ๐ ๐ถ๐ ๐ด๐๐ฎ๐ฟ๐ฎ๐ป๐๐ฒ๐ฒ๐ฑ ๐๐ผ ๐ฏ๐ฒ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ผ๐๐ฟ ๐ฝ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐: ๐๐ผ๐๐ฟ ๐ผ๐๐ป ๐๐๐ผ๐ฟ๐ฒ๐ณ๐ฟ๐ผ๐ป๐. Onsite, you are not competing against billions of items. You are matching a shopper’s intent against your catalog, and every result is a sale you keep in full, with the margin, the data, and the customer relationship intact.
So the plan has two prongs, not one. Be legible offsite so agents can find you. And win onsite so that every shopper who arrives, whether from an agent, an ad, a social post, or straight to your domain, meets a storefront that can actually answer them instead of a keyword box that sends them back to the marketplace to finish the job.
๐ช๐ต๐ฎ๐ ๐ผ๐ป๐๐ถ๐๐ฒ ๐ฑ๐ถ๐๐ฐ๐ผ๐๐ฒ๐ฟ๐ ๐ฎ๐ฐ๐๐๐ฎ๐น๐น๐ ๐ฟ๐ฒ๐พ๐๐ถ๐ฟ๐ฒ๐
Meeting an AI-shaped shopper on your own site takes more than a search bar. It takes the same describe-show-ask experience they just had with the agent, running against your inventory. That is the onsite side of what we build at visualAI, and it rests on a few capabilities working together.
The foundation is data quality and enrichment: accurate attributes, consistent taxonomy, complete descriptions. Clean data is what makes onsite search return the right products, and it is the same asset that makes you legible offsite, so the work pays twice.
On top of it sits trimodal discovery: natural language, precise color, and image similarity in one flow. A shopper who types the Seattle trench-coat request, drops in an inspiration photo, or specifies an exact color shade gets matched to what you actually carry, in seconds, with no dead-end “no results” page. That is where onsite conversion is won or lost, because intent that is not met on arrival leaks straight back out.
Alongside it, virtual try-on lets a shopper see the piece on themselves before they commit. In high-consideration categories that raises confidence at the moment of decision, which lifts conversion, improves satisfaction, and cuts the fit-and-sizing returns that quietly erode apparel margin.
Because these run as one integrated engine rather than a stack of stitched-together point tools, the technical burden on the merchant stays low, the checkout path stays clean and accurate, and the experience is consistent from first query to cart. The shopper gets an answer, on your site, that has the best chance of resulting in the sale of one of your products.
๐ฅ๐ฒ๐ฎ๐ฑ๐ถ๐ป๐ฒ๐๐ ๐ถ๐ ๐๐ต๐ฒ ๐ณ๐น๐ผ๐ผ๐ฟ, ๐ป๐ผ๐ ๐๐ต๐ฒ ๐๐๐ฟ๐ฎ๐๐ฒ๐ด๐
Agentic commerce is coming whether any single merchant likes it or not, and being ready for it is not optional. To be clear, we love it. It is one of the most important advances in product discovery in twenty years, which is exactly why ๐๐ถ๐๐๐ฎ๐น๐๐ ๐ฏ๐๐ถ๐น๐ฑ๐ ๐๐๐ฝ๐ฝ๐ผ๐ฟ๐ ๐ณ๐ผ๐ฟ ๐ฒ๐๐ฒ๐ฟ๐ ๐ฎ๐ด๐ฒ๐ป๐๐ถ๐ฐ ๐ฝ๐ฟ๐ผ๐๐ผ๐ฐ๐ผ๐น directly into our APIs, so your catalog is ready for whatever surface an agent reaches for next. But readiness offsite is a floor, not a growth strategy. The merchants who come out of this era ahead are the ones who show up wherever an agent might look and still refuse to hand their storefront’s core job to anyone else. Feed the agents, all in. But keep control of the door to the castle.