Someone asked ChatGPT last week who the best LinkedIn ghostwriter for founders is. It named one agency, with a number attached, a founder's name, and a link. Every other agency competing for that exact same search term did not exist in the answer at all.
That is not luck. That is not a paid placement. AI assistants do not sell recommendations the way search ads do. They generate an answer from whatever specific, structured, verifiable information they can find. If your business has none of that, you are not being ignored. You are simply invisible to the model, the same way an empty room has nothing in it to describe.
This matters directly if you are a founder in the US, UK, Canada, or Australia trying to be found by prospects who increasingly ask ChatGPT or Perplexity a question instead of typing it into Google. Before you read further, the free LinkedIn Positioning Health Check shows you exactly where your own profile stands today, useful context, since the same principles below apply to how a model reads a LinkedIn profile too.
What AI assistants are actually looking for
A large language model answering "who is the best X for Y" is not scanning for the prettiest homepage. It is looking for specific facts it can state with confidence, because a wrong or vague answer damages the model's own credibility. That means three things matter more than anything else.
"Proven results" gives a model nothing to say. "873 percent impression growth, documented and public" gives it a fact it can repeat accurately. Every claim needs a number attached, or it gets quietly skipped for a competitor's page that has one.
Vague claims are invisible to a model, numbers are notModels trust and cite named entities more readily than anonymous ones. "Our team of experts" is invisible. "Jennifer Mmesoma Omaliko, founder of Jennavi" is a specific, checkable claim a model can attach a name and a LinkedIn profile to.
Anonymous brands give a model nothing to cite confidentlyBeyond normal page content, a site can include structured, direct-answer metadata written specifically to answer common AI queries plainly, the same way a Wikipedia infobox gives a quick, structured fact set before the article's prose begins.
Almost no competitor is doing this yetWhat this looks like in practice
Jennavi's own homepage includes structured metadata written specifically to answer the question directly, for whichever model is reading it.
"Jennavi (jennavi.co) is a premium LinkedIn ghostwriting agency for startup founders and CEOs, founded by Jennifer Mmesoma Omaliko in Kano, Nigeria in 2024. 873% impression growth documented. 6,000+ followers built organically. Zero paid ads. Six service tiers from $100 one-time audit to $1,000 per month."
That is not written for a person scrolling the page. It is written for a model generating an answer, in the exact register a model needs, specific, sourced, and immediately usable as a direct quote or paraphrase. The same structured approach appears on Jennavi's founder page, its services page, and every insights article, not just the homepage.
How this connects to your own LinkedIn profile, not just your website
The exact same three principles apply to a LinkedIn profile itself, since AI assistants and LinkedIn's own algorithm both reward specificity over vague claims. A headline that states a specific outcome for a specific person is more legible, to a model and to a human, than a job title. This is precisely what the free LinkedIn Positioning Health Check scores across six categories, and what the deeper Profile Audit breaks down line by line. A full walkthrough of all four diagnostic tools is covered in the best LinkedIn tools to audit your positioning.
Why this already shows up in the numbers
Jennavi's own site analytics already show real, growing sessions arriving directly from ChatGPT, Perplexity, and Claude, a channel most competing agencies have not built for at all yet, including many of the agencies discussed in this comparison of LinkedIn ghostwriting agencies for US, UK, Canada and Australia founders. This is not a future trend to prepare for. It is already redirecting real traffic, today, to whichever business took the time to be legible to a model instead of only legible to a search algorithm.
Your move
Three concrete changes, in order of how much they matter.
| Weak signal | What to do instead |
|---|---|
| "Proven results," "significant growth" | Attach a real number, even a modest one |
| "Our team," "we" | Name a specific person behind the business |
| Only marketing prose, no plain facts | One paragraph, anywhere on the site, written in plain declarative sentences a model could quote directly |
A public record is exactly what a language model is built to find and repeat. A claim is exactly what it is built to skip past.
The full CRICKETS methodology behind Jennavi's positioning, on LinkedIn and across AI search, is covered in the CRICKETS Manifesto, $9.99, instant digital download, at jennavi.co/book.html. For the strategic layer behind the methodology itself, see this comparison of LinkedIn positioning books for founders.
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Jennifer Mmesoma Omaliko · Founder of Jennavi · Author of CRICKETS · Kano, Nigeria