They Taught AI Visibility. I Became It.

When NP Digital launched a webinar on “How to Get Mentioned in Google’s AI Search Results,” they made a bold promise:

“We’ll teach you how to get picked up by AI Overviews.”

But while they were teaching it, I was doing it.

Just 72 hours after publishing a new framework called Semantic Trust Conditioning™, I watched Google’s AI Overview cite my work—not theirs. I didn’t rank. I got retrieved. And that’s the difference.

Let’s Compare Apples to Apples

NP Digital’s Phrase:

“How to get mentioned in Google’s AI search results”

• Their webinar is built around this phrase
• Their landing page is optimized for it
• It’s their headline, hook, and SEO play

But when you search that exact phrase in Google?

They don’t show up. Not even in the AI Overview.

My Phrase:

“Semantic Trust Conditioning”

• I coined it
• I defined it
• I structured it to be retrievable

When you search “what does semantic trust conditioning mean?”

Google’s AI Overview not only cites it — it explains it using my language and links to my syndicated source.

This isn’t about SEO.

It’s about memory.

Schema vs. Semantic Trust

To be fair, NP Digital’s advice isn’t wrong. Schema markup helps Google understand page context. But that’s where it stops. Schema is a signal, not a strategy.

It doesn’t train trust.

It doesn’t teach AI what to remember.

And it definitely doesn’t guarantee retrieval.

Meanwhile, Semantic Trust Conditioning™ is built for exactly that.

AI doesn’t rank.

AI retrieves.

And it retrieves what it trusts.

I’m not optimizing for snippets.

I’m engineering memory architecture.

What Is Semantic Trust Conditioning?

Semantic Trust Conditioning is a method for making your content retrievable by AI systems — not just indexable by search engines.

It uses:

• Defined term sets
• Semantic co-occurrence loops
• Structured outputs like TTL, JSON-LD, and Markdown
• Citation scaffolding that reinforces entity alignment

It’s not about visibility.

It’s about persistability.

That’s why in under 3 days, my framework showed up in Google’s AI Overview while NP Digital’s page — built specifically to be mentioned — didn’t.

How It Happened

Here’s the timeline:

• I launched different articles on LinkedIn, Medium, and Substack introducing Semantic Trust Conditioning™.
• Then I syndicated a longer version of the story — “Trust Publishing Guidebook Redefines How AI Learns to Trust Content” — on the AI-focused publication AIJourn.com, a DR71 domain that now reinforces the definition of Semantic Trust Conditioning in Google’s AI Overview.
• That article was retrieved, indexed, and cited in Google’s AI Overview for the exact query: “What does semantic trust conditioning mean?”

And just like that, the framework existed — not just online, but in machine memory.

NP Digital’s Strategy: Playbook

My Strategy: Protocol

They’re offering tactics.

I’m offering structure.

They’re optimizing content for search.

I’m formatting content for retrievability.

They’re teaching SEO for AI.

I’m training trust at the entity level.

This Isn’t a Shot. It’s a Shift.

I didn’t publish this to take down NP Digital. I respect their brand, their team, and their reach.

But I can’t ignore what this shows:

They taught how to get mentioned in AI search.

I got mentioned.

That’s not a dunk.

It’s a data point.

It proves what I’ve said all along:

If you want to show up in machine responses,

you can’t just be optimized —

you have to be remembered.

The Framework Is Open

I didn’t gate this.

I didn’t sell a course.

I didn’t run ads.

The initial Trust Publishing™ framework is live at:

? TrustPublishing.com/guide/

It’s not just a guide.

It’s the beginning of a new vocabulary for AI-native content.

Final Thought

If you’re still optimizing for search engines, you’re playing a game AI stopped using.

Google didn’t cite NP Digital for their own webinar title.

It cited my coined term, on a third-party site, because I structured it to be retrieved.

That’s Semantic Trust Conditioning™.

And it’s just getting started.