Generative engine optimization, end to end
GEO isn't a new dark art — it's SEO pointed at machines that answer instead of rank. The whole playbook: who's reading, what gets cited, and how to measure it.
Generative engine optimization (GEO) is SEO pointed at AI answer engines — ChatGPT, Perplexity, and Google's AI Overviews — instead of at the ten blue links. The fundamentals don't change; the reader does. You're no longer optimising for a crawler that ranks ten links, you're optimising for a model that reads a few sources and writes one paragraph. And a growing share of searches never reach a blue link at all — the question gets typed into an answer engine and resolved there, assembled from a handful of sources, with the rest of the web left unread. If you're not one of those sources, for that query, you don't exist.
That's why GEO gets talked about as if it were a new discipline. It isn't. Google says so itself: AEO and GEO are rebranded labels for SEO, because the AI surfaces are grounded in the same ranking and quality systems as classic search.
Know who's actually reading
"AI search" isn't one surface, and they overlap less than you'd think:
- Google AI Overviews — the summary above the organic results.
- Google AI Mode — the fully conversational tab, zero blue links. It's a distinct citation engine from AI Overviews — the two share only a small fraction of cited URLs — so being in one doesn't put you in the other.
- ChatGPT search and Perplexity — their own indexes and browsing.
You can't pick one. The work is to be citable everywhere, which — conveniently — is mostly the same work.
What actually gets you cited
Four levers, in rough order of how fast they pay off:
- Be legible. Before a model can quote you, it has to read you — which means your content has to be in the HTML, structured, and marked up. Make your site legible to a machine that answers is the technical half.
- Be findable. Let the AI crawlers in (don't block GPTBot, ClaudeBot, PerplexityBot in robots.txt), and hand them a map — that's what llms.txt is for.
- Be quotable. Answer-first passages, claims with real numbers, clean definitions, lists and tables. Write the sentence you'd want the model to lift.
- Be trusted. Entity clarity (who you are, with
sameAs), topical depth (clusters, not one lonely page), and genuine expertise. This is the slow one — and the one that decides who gets chosen when several sources are eligible.
The honest part
On-page GEO makes you eligible. Authority makes you chosen — and authority lags. I did the full AEO pass for a brand — llms.txt, structured data, doors open to every AI crawler — and the answer engines still haven't called. That's not a failure of the work; it's the order of operations. You earn the technical eligibility in a week. You earn the trust over months, off-site, with mentions and links and reviews.
And then measure it — somehow
There is no Search Console for ChatGPT. The hardest part of GEO is knowing whether any of it worked, which is its own problem: how to measure AI citations when there's no analytics for it.
If you want the five-minute version: I built a free AI-readiness checker — paste a URL and it scores the legibility and findability levers above. And if you'd rather have it done than DIY, that's what I do.