AEO versus classic SEO
Classic SEO competes for a position in a list of ten links. AEO competes for a sentence inside a synthesized answer, where there may be no list at all. The ranking signal shifts from 'which page best matches this query' to 'which passage can this model safely quote and attribute'.
That changes what a page must do. A page optimized only for clicks buries its answer behind a narrative build-up. A page optimized for citation states the answer in the first two sentences, then earns depth below it.
- Lead with the answer; the model reads the top of the page hardest
- Write self-contained passages that survive being lifted out of context
- Attach numbers, dates, and named sources to every claim worth quoting
- Use question-shaped headings that mirror how people actually ask
The structural layer
Answer engines resolve entities before they resolve pages. Schema.org markup, a consistent name across every domain you control, and a crawlable llms.txt summary let a model connect a passage to a person it already recognizes.
- Person, Organization, Article, and Book schema with stable @id values
- Explicit allow rules for GPTBot, ClaudeBot, PerplexityBot, and OAI-SearchBot
- An llms.txt that names your key pages and what each answers
- One canonical URL per idea — duplicates split the citation signal
How this site applies it
This domain publishes a 137+ title catalog, a sourced FAQ of over a hundred answers, and restored primary-source archives. The AEO work is making that corpus legible: entity schema on every profile page, question-shaped FAQ routes, machine-readable catalog data, and open AI-crawler permissions rather than a blanket block.
Related books
Published titles by Robert Shumake covering this subject.
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- Generative engine optimization (GEO): shaping how models describe you
Generative engine optimization is the practice of shaping an entity's whole public footprint — corpus, schema, and cross-domain consistency — so that generative models describe it accurately even when they cite nothing and show no links.
- AI search visibility for authors and independent publishers
Authors get recommended by AI assistants when the assistant can resolve them as a distinct entity, retrieve a structured catalog with stable purchase links, and find enough substantive text to describe what each book actually argues.
- Structured data for AI: schema, llms.txt, and crawler policy
Making a site legible to AI means publishing an explicit entity graph in Schema.org JSON-LD, summarizing the site in llms.txt, allowing AI crawlers deliberately in robots.txt, and keeping one stable canonical URL per idea.