Answer Engines
6AIO / AI Mode: what publishers fault Google for
Online publishers have started a collective effort to document how Google's AI Overviews and AI Mode features affect them. They fault Google over how few sources it attributes, over the performance data it provides, and over an opt-out they say is not enough. Marketers should treat the sourcing and attribution rules inside AI answers as open and contested: what Google cites today can change under publisher pressure.
How to Set Up ChatGPT Shopping Ads
The post explains how to set up shopping ads in ChatGPT: a scrollable carousel of product cards at the bottom of a conversation, each showing brand, product name, price and availability. It argues the shopping format is worth more to sellers of physical products than the sponsored text placements that sit under an answer. Marketers selling products should set up the carousel and keep price and stock data accurate, since that is what the cards display.
Google’s AI Payment Pilot Vs. Cloudflare & Microsoft Models via @sejournal, @MattGSouthern
Google, Cloudflare and Microsoft are testing different ways to pay publishers when AI systems access or use their content, according to Search Engine Journal. The piece compares the three approaches, all of which are pilots rather than settled programs. Marketers should expect access deals to differ by platform, and should track which of their pages each program covers, since free crawling is not guaranteed to continue.
There Is No “Accuracy” in AI Search Tracking – Only Precision
Mike King argues that two AI visibility platforms reporting different numbers for the same brand, 41% versus 23% of the prompts that matter in his example, is not a case of one tool being wrong. He writes that AI search has no single true value to be accurate to, so teams can only compare the precision of tools built on the same definitions. Marketers should expect disagreeing AI visibility numbers from vendors and compare tools on method and consistency before putting a figure in a board deck.
Checking A Page Is Part Of A Retrieval Pipeline For AI via @sejournal, @chrisgreenseo
The post describes a way to check whether a page is being retrieved for AI answers: paste a distinctive snippet into a chatbot, ask for exact matches, and see whether your URL comes back. If it does, retrieval is not the problem, which matters because there is no Search Console equivalent for ChatGPT. Marketers can use the test to tell a retrieval problem apart from a citation or formatting problem before changing the page.
Agent-to-Agent Marketing
2WebMCP support now available in mcp-handler
Vercel's mcp-handler library now has experimental support for WebMCP, a proposed web standard for exposing tools to agents that run inside a browser. Adding one script tag makes a site's existing MCP tools available on the page, and calls are proxied back to the MCP server as the signed-in user, so tools that need a login work without a browser-side OAuth flow. Marketers should expect in-browser agents to act on site tools rather than only read pages, and can start deciding which product actions they want an agent to be able to take.
What brands need to survive agentic commerce
Appier's Korea enterprise sales lead describes buying that starts with a question to an AI agent rather than a search box, and cites a Morgan Stanley projection that orders placed through AI agents could reach 10% to 20% of US purchases by 2030. He says the starting point is connecting CRM, ecommerce and store data into one customer view, and pairing human sellers with sales agents. Marketers should plan for being found and chosen in every surface an agent checks, not for one ranked position.