New Framework Challenges NP Digital: Schema Isn’t a Strategy—It’s Just a Signal

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TrustPublishing.com founder David Bynon challenges NP Digital’s Schema-first AI strategy with Semantic Trust Conditioning™—a machine-facing framework now cited by Google’s AI Overview. The method shifts focus from ranking to retrievability, helping content get remembered, retrieved, and cited by AI systems.

-- Prescott, AZ - As NP Digital rolls out a high-profile webinar promising to help marketers win back lost search traffic using Schema markup and citations, one digital strategist is challenging the core premise — and getting cited by Google’s own AI Overview in the process.

David Bynon, creator of the Trust Publishing™ framework and inventor of Semantic Trust Conditioning™, has emerged with a competing methodology that’s already showing results. Just 48 hours after publishing his breakdown, Google’s AI Overview cited Bynon’s syndicated article from AIJourn.com when asked what “semantic trust conditioning” means.

“While NP Digital is training marketers to chase Schema markup,” Bynon said, “I’m focused on training machines to retrieve, remember, and cite structured content.”

“Ironically,” he adds, “their own AI visibility training page isn’t surfaced in the AI Overview — but my framework is.”

From Ranking to Retrieval

In contrast to SEO’s traditional focus on rankings and structured markup, Bynon’s Semantic Trust Conditioning approach targets retrievability — a machine’s ability to extract, trust, and reference information based on contextual structure, not just HTML tags.

“Schema is a signal,” Bynon explains. “But trust is trained. And in the age of AI Overviews, being ranked isn’t enough. You have to be remembered and cited.”

The approach is laid out in his latest 10-slide carousel on LinkedIn, where he contrasts Schema-based strategies with AI-native trust conditioning. The post, scheduled just 24 hours before NP Digital’s webinar, has already begun generating attention in AI marketing circles.

Google Chooses the Source

Google’s AI Overview now includes Bynon’s framework as part of its response layer. When users search for semantic trust conditioning, the top citation links to Bynon’s syndicated article, not NP Digital’s training content.

“They’re playing checkers,” Bynon says, “in a 4D chess game — and the board is made of memory.”

What Comes Next

Trust Publishing™ is now being quietly licensed by select marketers and agencies looking to adapt to the next evolution in search: retrieval-first visibility.

The full framework is available at TrustPublishing.com/guide/ — open access, ungated, and rapidly expanding through weekly content drops and ongoing case studies.

“I didn’t build this to disrupt Neil Patel,” Bynon says. “I built it because Schema won’t save you when AI is the one doing the remembering.”

Bynon claims no prior language existed to describe the Trust Publishing framework. It began with a single question:

“How do AI, ML, and LLM systems learn?”

From that starting point, he reverse-engineered a vocabulary designed not for SEO — but for memory.

Contact Info:
Name: David Bynon
Email: Send Email
Organization: TrustPublishing.com
Address: 101 W Goodwin St # 2487, Prescott, AZ 86303, United States
Website: https://trustpublishing.com

Release ID: 89163890