Agentic commerce, explained

Fixes

• How to write product copy an agent can parse

  Product copy helps an agent where it states a fact that can be checked against a shopper’s constraint, and does nothing where it makes a claim that cannot be verified. That does not mean writing for machines: it means making sure the specifics a buyer needs, materials, dimensions, compatibility, care, are present as plain statements somewhere, alongside whatever persuasion the page is doing.

• How to structure collections for agent discovery

  Collections organised around how a business buys and merchandises stock rarely match how shoppers describe what they want, so a request for a kind of product resolves to a homepage rather than to a set of yours. Structuring for discovery means having a real page for the categories people actually ask for, and making sure those pages are listed, crawlable and readable without scripts.

• How to keep a product feed fresh

  A stale product feed is worse than no feed at all, because an absent feed sends an agent to your pages while a stale one gives it a fast, confident, incorrect answer it has no reason to double check. Freshness is therefore a property to monitor rather than a job to schedule, and the failure is silent: the URL still resolves and the file still parses.

• How to test checkout in an in-app browser

  When an assistant sends a shopper to your checkout, the purchase often completes inside an in-app browser rather than in the shopper’s usual browser. That environment is narrow, cold, and restricted in ways ordinary mobile testing does not reproduce, so a checkout that passes every device test you run can still fail the sessions an assistant actually sends you.

• How to make add to cart work without JavaScript

  An add to cart that only works once scripts have run is unusable to any agent that stopped at your markup, and agents take the cheapest path to an answer rather than rendering every page. A form that posts to a server side endpoint is the fallback that makes the action expressible, and it costs nothing visible: the scripted version can still enhance it for everyone else.

• How to stop popups blocking agent checkout

  An agent arrives with no cookies and no history, so every modal your store shows to a first time visitor fires on every visit. A newsletter overlay, a consent wall, a region selector or a cart upsell that a person dismisses without thinking is an unanswerable obstacle to an agent, and it usually appears at exactly the point where a purchase was about to complete.

• How to offer guest checkout for agents

  An agent will not create an account, so a checkout that requires one converts a won sale into no sale at the last step. Most forced account creation exists for reasons that guest checkout can satisfy anyway: order lookup, marketing consent and repeat purchase are all achievable without making registration a precondition of paying.

• Cloudflare settings for AI shopping agents

  Cloudflare separates bot traffic into categories, and the setting that governs shopping agents is usually one somebody accepted once rather than chose. That matters because this layer enforces where robots.txt only requests, so a store can publish a welcoming robots file and still block every agent that honours it.

• How to let honest agents through bot protection

  Bot protection is the earliest and bluntest way a store disappears from agentic shopping: a challenge that asks the visitor to enable JavaScript and wait is unanswerable to an agent, so every other quality of the store stops mattering. The work is separating identifiable, well behaved agents from the abusive traffic the protection was bought for, which is a policy question rather than a technical one.

• How to make variant pickers agent accessible

  A variant picker fails an agent when the options only exist after a script attaches them, or when selecting one requires a hover. Both leave an agent at a product it wants and unable to say which version it wants, which is the most expensive place to fail because everything before it succeeded. Most of the remedy is ordinary accessibility work you may already owe.

• How to publish policies as text, not images

  A policy set in a designed graphic is unreadable to an agent, which means an agent asked whether you offer free returns will answer that you do not say. That is a different and worse answer than no, because a store with a stated but restrictive policy beats a store whose policy cannot be read. Converting them is a template change, not a design sacrifice.

• How to publish shipping costs machine readably

  An agent comparing stores needs the delivered total, not the item price, and it will not guess generously when your shipping cost only appears at checkout. Publishing shipping as data before checkout is what turns you from an unknown into a comparable offer, and the common objection, that shipping is too complicated to state, is usually about edge cases rather than the ordinary case.

• How to expose stock availability to agents

  Availability is only useful to an agent when it is stated per variant and when it is accurate in the negative. Stores routinely publish availability that is correct while a product is in stock and silently wrong once it is not, or that describes a product rather than the size a shopper asked for, and neither error is visible to anyone testing with a product that happens to be available.

• How to add GTINs to your catalogue

  A GTIN is a global identifier that lets an agent recognise your product as the same item it has seen on another store, which is what makes a price comparison possible at all. Without one you can still be found, but you are compared as an unknown rather than as a competing offer on a known product, and unknowns lose.

• How to publish a product feed for AI agents

  A product feed lets an agent read your whole catalogue in one request instead of fetching and parsing every product page. That matters because an agent answering a question does not survey your store, it takes the cheapest path to an answer, and a store that is expensive to enumerate gets skipped rather than ranked lower.

• How to configure robots.txt for AI shopping agents

  Search crawling, training data collection and agentic shopping are three different uses with three different consequences, and most robots.txt rules about AI were written with only the second in mind. The result is stores that intended to keep their content out of a training set and also removed themselves from assistant driven purchases, without ever making that decision.

• How to write an llms.txt for an online store

  An llms.txt file is a short, machine readable map of what a site contains and where the authoritative version of each thing lives. For a store it is most useful pointing at your policies, your feed and your reference pages, not at your catalogue, which belongs in a feed. It grants no permission and replaces nothing: robots rules still decide access, and structured data still decides whether a product is legible.

• How to add product schema for AI agents

  Product schema is how you state your price, availability, identifier and terms as data rather than as layout, so an agent reading your page does not have to infer them. Adding it is usually a template change rather than a redesign, and the test of success is not that the markup validates but that the specific facts an agent needs are present in it.