Resources
Comparison
Honest comparisons, including the cases where we are not the right answer.
Product schema answer engines can actually read
Attribute coverage, offers, reviews and FAQ markup, plus the validation step most stores skip.
llms.txt and agents.md: what to publish and what it does
The machine-facing layer, what belongs in it, and what it will not fix on its own.
Merchant Center in both directions
Google for Gemini and AI Overviews, Microsoft for ChatGPT and Copilot, and why feed quality decides both.
Metafields as the attribute layer
Turning specs buried in description copy into structured attributes an engine can quote.
Crawl access for AI agents without opening the door to everyone
robots.txt, agent user-strings, and the trade-offs of each choice.
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