Started writing this at the airport in Bali, now in Amsterdam for the event where I'm giving the Unmuted talk I've been posting about.
Rice fields to a conference stage in under a day.
(The beauty of the online world we live in.)
So this one has been in the works for a while.
I've spent the past few weeks researching and digging into this.
How to rank on AI using LinkedIn.
Why this matters
Think about how your buyers look for someone now. They open ChatGPT or Perplexity, ask a specific question, and the answer names a handful of people or companies. If you're one of them, you're on the shortlist before a single call happens.
Her headline leads with the exact niche: battery thermal safety, advisor to BESS, EV, and insurance risk teams, with real numbers attached, like EUR 30M in risk resolved.
So when a risk lead asks an AI who can advise on battery thermal safety for a BESS project, her profile is matchable. It names the precise thing they typed.
A profile that just said safety consultant matches nothing.
That is the whole point of citation. 84% of B2B buyers in a recent survey said they use AI search while making buying decisions. The source AI cites shapes how it describes your space, often close to your own words.
If you're not the cited source, your competitor is.
What's inside
I built a FREE TOOLKIT to get your content into those answers. Five prompts you paste into ChatGPT or Claude:
Audit your profile so AI can read and cite it
Rewrite a post to match the questions buyers ask AI
Turn one broad topic into ten niche angles
Convert a blog post into a LinkedIn article, the format AI cites most
Map the exact questions your buyers type into AI
I already have your guys’ email lol just for you guys to see what you’ll get
It's built on the two 2026 studies that analyzed more than 100,000 LinkedIn URLs and posts cited in AI search, from Semrush, Scrunch and LinkedIn.
None of it guarantees a citation.
It improves your odds because it’s built from the actual studies.
The one move I'd start with
Copy your existing blog posts into LinkedIn articles.
It gives you a second surface that feeds both AI search and Google. Articles are 50 to 66 percent of cited LinkedIn content, and almost nobody is running it.
My friend Jake Ward pushes this idea further.
He calls it tri-publishing: write one strong, opinionated article, then put it natively in three places.
On X for reach
As a LinkedIn Pulse article for search and AI citations
As a longer version on your own site for keywords you own
One piece of writing, three surfaces.
His own article on programmatic SEO is the proof. The X version pulled hundreds of thousands of views for reach, and the LinkedIn Pulse version of the same piece ranked at the top of Google for its keyword and started turning up in ChatGPT and Perplexity answers.
Same article, two different jobs.
The Pulse version carries the most weight for citations, because it sits on a domain Google already trusts and it's the format LLMs pull from most.
Get on the lists AI already cites
Jake Ward looked at where AI citations actually come from and found that close to half point to best-of style pages: best-X roundups, alternatives pages, and comparisons.
When a buyer asks an AI for the best tool, agency, or person in your category, those pages are what it leans on.
For example, John Shehata's The Best SEO & News SEO Newsletters I Actually Read Every Week is one of the most-cited LinkedIn URLs in Semrush’s study.
Every section answers a specific question on its own, which is the kind of structure AI keeps pulling from.
So two moves.
Get onto the third-party lists that already rank in your space, the ones your buyer would land on.
And publish your own: a best-of, an alternatives page, a side-by-side comparison. Keep them current, because AI favors pages that were updated recently.
Use the same words every time
Pick your vocabulary and hold it. When you describe your category, your product, and your niche the same way in every post, AI starts to associate you with that space. When you swap the terms around from post to post, that association never sets.
A few ways to keep it tight:
Write your terms down. The category name, the product names, the words you use for what you do. Share that list with everyone posting under your brand, execs and ghostwriters included.
One word per idea, and commit. If your category is "AI search visibility," don't drift to "generative search SEO" three weeks later. Hold the line even when a competitor uses a different label.
Describe your product the same way everywhere. Employee posts, the company page, and customer stories all reading alike.
Ina Nikolova is a good example. She gets cited across multiple AI engines for cybersecurity because she owns a clear vocabulary lane: PAM (privileged access management), managed services, and identity.
These articles literally have like 5 likes.
And it doesn't matter for citations.
Scrunch studied 12,000 LinkedIn posts ChatGPT pulled from as sources, and reaction count had near-zero effect on whether a post got cited.
So what did she do well?
She uses the same terms across her articles, “How modern PAM solutions enhance cybersecurity” and “How do managed services help reinforce security”, and she defines her key terms every time.
That repetition is what teaches AI to connect her name with the topic.
A little extra something today
I'm not an engineer, and I still built this tool. I described what I wanted in plain English, Claude built it as a working tool I could use right away, and I shaped it by talking: “make the headline option lead with the role”, “the article is cutting off so fix it”, “stop flagging formatting that isn't there”.
A few hours of back and forth, and it was done.
A few years ago an idea like this sat in a doc until you could pay a developer or learn to code.
Now a marketer with a clear idea can build the actual thing.
If you want to try it yourself, the feature is called an artifact. Open Claude, describe the tool you wish existed (something like, a tool that takes my draft post and rewrites it to be more citable), and it writes a live version right there in the chat.
You don't read the code. You use it, tell it what's wrong, and it changes.
Start with one small task you do by hand every week. That's usually the best first build.
Get the toolkit
GRAB THE TOOLKIT HERE - Free, no hoops :)
If you'd rather have the whole content engine built and run for you, that's Distinctiva: distinctiva.io.
If you want to build it yourself, week by week, that's The LinkedIn Engine: skool.com/the-linkedin-engine.
See you in the next one,
D.