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Plain-English thinking on AI visibility, GEO, and how brands get quoted.

This is where we write about generative engine optimisation — the practice of getting your brand quoted when someone asks ChatGPT, Gemini, Claude or Perplexity a question your business should be the answer to. It is a young field, most of the advice circulating in it is guesswork, and a lot of it is recycled search-engine folklore with the word "AI" pasted on top. We try to write the other kind of piece: what we can actually observe about how the assistants answer, and what we can't.

Expect four recurring themes. Measurement — how to tell whether an assistant cited you, how to separate a real movement from a noisy week, and why analytics alone won't show you any of it. Diagnosis — the page-level reasons an engine skips you: thin or buried answers, missing structure, content that reads well to a person but parses badly to a model. Structured content — FAQ and schema markup, question-led headings, and llms.txt, the emerging file that tells AI crawlers which pages on your site matter. And proof — showing what a change actually achieved.

Everything here is written in plain English, with the evidence and the limits stated. If something is still uncertain, we say so.