How answer engines pick their sources, how to write for them and how to measure your own visibility inside them at all.
What goes into an llms.txt, how it differs from robots.txt and sitemap.xml, how widespread support actually is — and an honest assessment of the effort.
What an entity is, why consistent details across several sources matter more than any single optimisation, and the seven steps to a clear company profile.
The six properties cited sources have in common — and the three reasons substantively strong pages still never appear in an answer.
Which crawlers exist, how collectors and runtime fetches differ, and which three strategies suit which business model.
Answer first, evidence after — with right-and-wrong comparisons, the six phrases that make a paragraph unquotable, and a checklist before publishing.
How to recognise AI traffic, how to separate it cleanly from other sources, what the server logs add — and where the measurement honestly ends.
A repeatable procedure with a fixed question list, clean testing conditions and an evaluation that turns into concrete tasks.
Every system cites differently — different sources, different currency, different willingness to name small providers.
Four types cover most business sites — three you can skip. Where they go, how to check them, and the mistake that quietly invalidates everything.
Search engine and answer engine optimisation side by side — the overlaps, the real differences, and one concrete list of measures for each.
Answer engines cite sources by different rules than search engines rank. What changes compared with classic SEO — and the six measures that work.
