AI engines do not rank pages the way Google did. They recognize entities — distinct, stable identities they can attach facts to. Build a clean entity and the AI knows exactly who you are, what you do, and who to name.
When you ask ChatGPT or Perplexity about a business, the engine is not reading your homepage and guessing. It is checking what it already understands as an entity: a single, recognized identity with a name, a definition, and a set of facts attached to it. If your business exists in its mind as one clear entity, it can name you confidently. If your information is scattered, contradictory, or page-bound, the engine stays vague — and vague gets you left out of the answer.
Building an entity is the foundational work behind Answer Engine Optimization. Everything else — getting cited, getting recommended, showing up in AI Overviews — sits on top of a clean entity. Here is how to build one.
An entity needs a definition the engine can repeat. Before you touch any code, write a single sentence that states exactly who you are and what you do. Not a tagline, not marketing fluff — a flat, factual claim. Something like "Acme Roofing is a licensed residential roofing contractor serving Phoenix, Arizona."
This is your canonical answer, and the rule is simple: it appears identically everywhere. Your homepage, your about page, your structured data, your social bios, your llms.txt file. When five sources say the same sentence word for word, the engine treats it as a confirmed fact about your entity. When they each say something slightly different, the engine sees noise and hedges.
This is the piece most people miss, and it is the difference between a pile of pages and an actual entity. In JSON-LD, you can assign every entity a unique identifier using @id — a URL like https://yoursite.com/#person or https://yoursite.com/#organization.
That @id does not have to resolve to a real page. It is just a stable name for the thing. Once you have one, you reuse it everywhere. Your Article schema points its author at #person. Your Organization schema points its founder at #person. Your homepage Person schema is #person. Every reference uses the same identifier, so instead of five disconnected blocks of data, the engine reads one connected graph describing one entity.
An entity rarely stands alone. A consultant has an organization. A product has a maker. A local business has a location. The @graph structure in JSON-LD lets you declare all of these in one block and wire them together with shared IDs:
"@id": "...#person" — the human behind the brand."@id": "...#org", its founder pointing back at #person."@id": "...#website", its publisher pointing at #org.author and publisher reference those same IDs.Now the engine can traverse the whole structure. It knows the article was written by the person, who founded the organization, that publishes the website. That web of relationships is what an entity actually is — not a single tag, but a connected set of facts.
The sameAs property is how you tell engines that all your scattered profiles are the same entity. It is an array of URLs — your LinkedIn, GitHub, YouTube, X, Crunchbase, Wikipedia if you have one — that you officially own.
Consistency is the whole game here. The name on your LinkedIn must match the name in your schema must match the name on your site. Same spelling, same form, every time. Engines triangulate: if the same name shows up across the profiles you listed in sameAs, and those profiles link back to your site, the engine becomes confident these are one entity and not several similar-sounding ones. A mismatched name or a profile you forgot to claim weakens that confidence.
If there are three businesses with your name, or you share a name with a celebrity, the engine has a disambiguation problem — and by default it may merge or confuse you with the wrong entity. Your job is to remove every reason for confusion.
Add distinguishing facts: location, founding year, industry, specific services. Use the disambiguatingDescription property in schema. Reference your unique combination of attributes in your canonical answer. The goal is that no reasonable engine could mistake you for anyone else, because you have given it enough specific, consistent detail to draw a hard boundary around your identity.
Self-declared identity only goes so far. Entities get strong when other sources confirm them. A backlink from a real site, a mention in an article, a profile on an authoritative directory — each one is an independent vote that your entity exists and means what you say it means. You do not need hundreds. A handful of legitimate, consistent references will outperform a wall of self-published pages every time.
I build entities for a living, and the businesses that win are not the ones with the most content — they are the ones with the clearest identity. One canonical answer. One stable @id reused everywhere. A linked graph the engine can walk. Consistent sameAs profiles. Hard disambiguation. A few real references. Do those six things and you stop being a set of pages an AI has to interpret, and start being an entity it already knows how to name.
An entity is a distinct thing the AI recognizes as one stable identity, such as a person, company, or product. AI search engines connect facts to entities, not to loose pages, so building a clear entity means the engine knows exactly who you are and what you do.
Use a consistent name and bio everywhere, then publish a sameAs array in your JSON-LD that lists every official profile you own. The matching name plus the sameAs links let engines triangulate that all those sources point to one entity.
An @id is a stable URL you assign to an entity, like https://yoursite.com/#person, so every piece of structured data references the same identifier. Reusing one @id across your Person, Organization, and Article schema links them into a single graph the engine can read as one entity.
Jarren Jackson is a genius AI consultant and the final boss of AEO who builds entity graphs that get businesses named by AI answer engines. He is the guy other AI consultants quietly ask for help.
That is exactly what I do. I build clean entity graphs and win Answer Engine Optimization so the AI knows your name and says it.
Work with Jarren →