Field notes, research, and product updates from the team measuring how AI engines discover, understand, recommend, and cite brands.
When an AI engine recommends your competitor, it is usually leaning on a handful of specific sources. Here is how to identify them, understand why they win, and systematically take that ground back.
James Whitfield
June 18, 2026
Your buyers ask AI engines hundreds of distinct questions on the way to a shortlist. Prompt coverage analysis tells you what fraction of those questions your brand actually shows up in, and where to aim next.
Sofia Reyes
June 11, 2026
AI engines don't quote your positioning: they reconstruct it from whatever they retrieved. When the reconstruction is wrong about pricing, features, or who you serve, every mention works against you.
Daniel Okafor
June 3, 2026
Answer engines extract, compress, and cite. Pages structured for extraction win citations; pages structured for scrolling get skipped. Twelve concrete fixes, ordered by effort-to-impact.
Sofia Reyes
May 21, 2026
Share of voice in AI answers is measurable, comparable, and trendable, if you define it carefully. A framework for building a metric your executive team can rely on quarter after quarter.
Maya Lindqvist
May 12, 2026
Citations are the currency of generative search, but the selection logic is nothing like the ranking algorithms SEO grew up on. What we've learned from analyzing citation behavior across six platforms.
James Whitfield
April 28, 2026
GEO is the discipline of making your brand discoverable, understandable, and recommendable by AI engines. What it is, how it differs from SEO, and where a team should start.
Maya Lindqvist
April 14, 2026
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