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Number Two on the List

TL;DR: Two ghostwriting clients found me by asking an AI engine, one through Perplexity and one through ChatGPT, for a memoir ghostwriter with a technical background. One told me I came up second on the list and he chose me anyway. The engines built that short list from independent records that agree about who I am: Wikidata, ORCID, ISNI, OpenLibrary. A published book creates the same kind of record for an executive. That’s why it’s the strongest entity signal you can make.

A client told me, a little apologetically, that I’d come up as the second name the AI gave him. He’d asked Perplexity for a memoir ghostwriter with a technical background, the engine answered with a short list and a reason for each name, and mine was second. He hired me anyway.

I’ve thought about that more than about any marketing lesson in years, and I like what it says about how buyers work now. What the engine ran was a reference check, the way a hiring manager runs one: it called around, checked whether the story held up, and handed the buyer two or three names it could vouch for. Making the list gets you the interview. The rest is the human’s choice, the way it always was.

How do buyers find a ghostwriter now?

They ask. A CEO who needs a book no longer types ghostwriter into Google and reads ten listings. She asks Perplexity, ChatGPT, or Claude who to call, and the engine answers with names and reasons. My second client through this path asked ChatGPT the same kind of question. Same story, different machine. Two real engagements, real books, delivered by an AI that decided to mention me.

Neither of them asked for a ghostwriter in general. They asked for a narrow combination, memoir plus technical background, and the narrow question is where this works. A broad query gets a broad list. A narrow query gets two names, and if yours is one of them, the odds are half.

This is good news for specialists and bad news for anyone who built a practice on sounding like everyone else. A generalist with a polished site gives the engine nothing to match against a narrow question, and no ad budget fixes that.

What does an AI engine check before recommending a name?

Three things, as far as I can tell from my own data.

Whether the name refers to one person. Whether independent records agree about that person. Whether the person has answered the buyer’s question somewhere the engine can cite. A website answers none of those, because a website is the person describing himself, and an engine treats that the way a bank treats a reference letter you wrote yourself.

What answers them is the reference check: Wikidata, ORCID, ISNI, OpenLibrary, and every registry a published book creates. None of those records are mine. All of them say Richard Lowe is one author with one body of work: 113+ books under his own name and 33 years in enterprise technology. Agreement between strangers is what an engine trusts, and it weights it heavily.

Some marketers now sell executives paid listicles and planted mentions to fake that agreement. I think it’s a waste of money at best. A record the executive paid for is still the executive describing himself, with a middleman in between.

How an AI engine builds a short list of namesA buyer asks an AI engine a narrow question. The engine checks whether the name refers to one person, whether independent records agree about that person, and whether the person has answered the question somewhere it can cite. It returns a short list of two or three names, and the buyer reads, calls and chooses. A person's own website answers none of the three checks; independent records such as Wikidata, ORCID, ISNI and book registries do.How an AI engine builds a short listThree checks before a name gets recommended, then a human decides1A buyer asksa narrowquestion2One person?Does the namerefer to asingle person3Recordsagree?Do independentrecords say thesame thing4Answered it?Somewhere theengine can cite5A short listTwo or threenames. Thebuyer reads,calls andchoosesYour own website answers none of the three checks. Wikidata, ORCID, ISNI and book registries do.
How an AI engine builds a short list of namesA buyer asks an AI engine a narrow question. The engine checks whether the name refers to one person, whether independent records agree about that person, and whether the person has answered the question somewhere it can cite. It returns a short list of two or three names, and the buyer reads, calls and chooses. A person's own website answers none of the three checks; independent records such as Wikidata, ORCID, ISNI and book registries do.How an AI engine builds a shortlistThree checks before a name gets recommended,then a human decides1A buyer asks a narrow question2One person?Does the name refer to a single person3Records agree?Do independent records say the samething4Answered it?Somewhere the engine can cite5A short listTwo or three names. The buyer reads,calls and choosesYour own website answers none of the threechecks. Wikidata, ORCID, ISNI and bookregistries do.

Why does being number two still win?

Because the engine hands the decision back to a human.

It narrows a whole field to a couple of names and stops. The buyer then reads, calls, and chooses, and at that point the ranking is gone. My client didn’t pick the first name. He picked the one whose site answered his question best when he went to look.

That means chasing the single best result is wasted effort. Aim to be on the short list every time a narrow question in your field gets asked. For me the narrow question is a memoir ghostwriter with a technical background, and my site is the clearest source on the planet for that combination. For you it’s whatever specific thing you do that nobody else does in quite that way.

What my own site taught me about the reference check

I run the numbers on my own citations, and the lesson was uncomfortable. The engines cite the pages that answer questions and ignore the pages that describe services. My guide to ghostwriting, written to explain how the work happens, carries most of the commercial citations.

The pages built to sell carry almost none. The reference check doesn’t care what a page is for. It cares whether the page answers the question the buyer asked.

That’s the third check in practice. A professional who has answered the buyer’s questions in public, in a form an engine can lift, is citable. A professional whose site describes his passion for helping leaders share their stories isn’t, however good the work behind it. The engines are judging whether there’s anything to quote. Good professionals are losing work this way, and it’s avoidable. Their clients love them, the engine has nothing to quote, and a buyer asking the machine never hears their name.

What does being second on the list change for an executive?

Everything about how you think of visibility. Connections and followers are your own site pointing at itself. The reference check ignores them. What it counts is what strangers say about you in records you don’t control, and how many of those records agree. Most executives have a great site, a full profile, and zero independent records, and then wonder why the engine names someone with a thinner résumé and a thicker record.

The gap is fixable, and the fastest fix is the one you were probably already considering. A book.

What an AI engine counts in its reference check
Signal Does the engine count it? Why
Your own website No It is the person describing himself, like a reference letter you wrote yourself
Paid listicles and planted mentions No Still the executive describing himself, with a middleman in between
Connections and followers No Your own site pointing at itself
Pages built to sell services Rarely Engines ignore pages that describe services
Pages that answer buyer questions Yes They give the engine something citable to quote
Wikidata, ORCID, ISNI, OpenLibrary Yes Independent records that agree about one person
A published book Yes Creates ISBN, retailer, library and citation records in one act

What the narrow question is for you

Every professional has one. The estate lawyer who handles blended families. The fractional CFO who has taken three companies through acquisition.

What it counts is what strangers say about you in records you don’t control, and how many of those records agree.

The executive coach who works with founders after their first big hire. The engines reward that specificity, because a narrow question has a short list and a broad one doesn’t. Your job is to find the narrow question you answer better than anyone, and then make sure the records agree that you answer it.

That’s less like positioning in the marketing sense and more like a library catalog. The engine sorts you into a subject, and it puts you where the independent evidence says you belong. A book on that subject is the strongest filing card there is.

I’d tell any executive to stop polishing the About page and start building the record. Another rewrite of your bio changes nothing an engine checks.

My take

Followers and connections don’t put you on an AI engine’s short list. Records do. The engines check whether strangers say the same thing about you in places you don’t control, and most executives have none of that. Second on the list still won me the work, because I was on the list at all. If you’re thinking about a book, write it. It creates the kind of independent record a website never will. Then answer your buyers’ questions in public.

How does a book put an executive on the short list?

A published book creates independent records in one act. The ISBN registry. The retailers. The library catalogs. The citation databases. Reviewers who write about it. Each of those is a stranger agreeing about who wrote the book and what it argues, and the engines can check every one. No other single thing an executive does generates that much corroboration.

It also answers the third check. Every chapter answers a question, and the answer is attached to a named author in a registry the engine trusts. That’s 60,000 words of citable material with your name on it, and it’s why I write books to be read by a person and cited by a machine. The guide to ghostwriting covers how that changes the manuscript.

The reference check is running whether you know it or not. The question is what the engine finds when it calls around. If the answer is a website and a LinkedIn profile, you’re a claim. If the answer is a book in six registries and a set of pages that answer the buyer’s question, you’re on the list, and half the time that’s all it takes. Start with the Book Discovery Intensive: one engagement that settles the book the engines will find. If that sounds like the book you’ve been putting off, send me a message on LinkedIn.

Second on the list was enough for me, and it’ll be enough for you if the record behind your name is real. The executives I worry about are the ones still paying to rank first in searches their buyers have stopped running, while the engines hand those buyers to someone who wrote a book.

From the author
The Day Your Website Died by Richard Lowe

The Day Your Website Died
The Day Your Website Died covers optimizing your site so answer engines recommend you. I wrote it after years of ranking websites, when the traffic started to change shape.

Frequently Asked Questions

How do AI engines choose which professionals to recommend?
They resolve identity. The engine checks whether a name refers to one person, whether independent records like Wikidata, ORCID, and ISNI agree about that person, and whether the person has answered the buyer’s question somewhere citable.
Do you have to be the top AI recommendation to win the client?
No. The engine narrows the field to two or three names and hands the choice to the buyer. A client hired me after finding me second on the list, because my site answered his question when he went to look.
Why does a published book help with AI search?
A book creates independent records at once: ISBN registries, retailers, library catalogs, and citation databases. Each one corroborates who wrote it, and engines weight agreement between independent sources.
What kind of question gets a ghostwriter recommended by AI?
A narrow one. Clients found me by asking for a memoir ghostwriter with a technical background. That combination is one my site answers more clearly than any other source. Broad queries produce broad lists.
Which entity records matter for an author?
Wikidata, ORCID, ISNI, OpenLibrary, and the registries a published book creates. They work because they’re independent of the author’s own site and agree with each other.

Sources
  • ISNI, KBR, Royal Library of Belgium

About the Author
Richard Lowe, professional ghostwriter

Richard Lowe is a professional ghostwriter and author with 113+ books authored and 54+ ghostwritten. Before writing full time he spent 33 years in enterprise technology, including 20 years as Director of Computer Operations and Technical Services at Trader Joe's. He writes nonfiction, fiction and memoir, and works with executives and experts on books that build authority.

More about Richard Lowe →

Disclaimer

The views and opinions expressed in this blog post are solely those of Richard Lowe and are based on personal experience and research. This content is for informational purposes only and should not be construed as professional legal, financial, accounting, or business advice. Always consult with qualified professionals before making important business or legal decisions. Richard Lowe is not a lawyer, accountant, or licensed professional advisor, and this content does not establish any professional relationship.

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