Because execution, not information, is what clients buy: the patterns above are visible on every page of our 40-site network, and knowing them is different from applying them across a thousand pages with verification discipline and editorial judgment. Publishing the playbook also keeps us honest — an agency whose methods cannot survive daylight is selling something else.
Mechanics questions
What actually makes content citeable by AI engines?
The recurring pattern across engines: a direct answer near the top, sized for extraction (we build 40-60 word answer blocks); headings shaped like the questions people ask; specific dated facts a system can attribute ("verified X on DATE from SOURCE" beats vague claims); consistent entity naming so the engine knows who is asserting; and machine-readable surfaces — schema that matches visible content, llms.txt that hands engines the map. None of it is secret; all of it is work.
Is llms.txt actually used by AI systems?
Honestly: adoption by engines is uneven and evolving, and anyone claiming llms.txt is a ranking key is ahead of the evidence. We ship it anyway, for defensible reasons — it is nearly free, it concentrates your citeable facts where crawlers and agents increasingly look, and our own network uses it as the canonical citeable-facts layer per site. Cheap, harmless, plausibly compounding: that is the honest case.
How long does AEO take to show results?
Structural changes are crawlable within days-to-weeks, and citation behavior shifts on the engines' own opaque schedules — we have seen priority-query citations move within weeks and others resist for months. Anyone quoting a precise timeline is quoting their hopes. The commitment we make instead: a measurement baseline before work starts, so whatever moves is visible and attributable.