 | We built a free, static-only scanner — 18 checks, no API calls, just HTML analysis. Then we pointed it at five brands that obsess over customer experience: Glossier, Allbirds, Gymshark, Drunk Elephant, and Brooklinen. Every brand has clean structured data. Prices are server-rendered. No prompt injection. Robots.txt is open. The data layer works. But the moment an agent tries to do something — pick a size, add to cart, search for another product — it hits a wall of custom JavaScript that has no semantic meaning. Gymshark is the most striking. Three million monthly visits, Gen Z audience (the demographic most likely to use AI shopping agents), and their homepage has no search form an agent can find. The size picker is invisible to non-browser clients. The cart API returns nothing. An agent trying to buy a $30 t-shirt would fail at every interaction step. The revenue math is uncomfortable. If 5-15% of traffic is AI-referred (Gartner's 2027 projection), and these agents convert at 2-4% when they work, these five brands are collectively leaving $82,000 to $491,000 per month on the table. Not because their products are bad or their pages are ugly — because their size pickers use <div> instead of <select>. The fix is boring. Semantic HTML. A 20-line llms.txt file. Re-enabling the Shopify cart API that was on by default. The brands scoring highest in our 17-brand leaderboard (Kylie Cosmetics: 100, Framebridge: 96) aren't doing anything exotic. They're just using <select> elements and standard forms. The gap between "a beautiful page" and "a page agents can shop" is about a day of developer time. The question is which brands close it first. Scanned July 2026 with https://github.com/monkrus/agent-a. 18 static checks. Scanner is open source. [link] [comments] |
Predictive technology: computational social science
