A 20-year observation: Why AEO sometimes fails (and the "Trust Layer" I’m adding) · AEO

A 20-year observation: Why AEO sometimes fails (and the "Trust Layer" I’m adding)

Hey everyone,

I’ve been diving deep into the AEO Blueprint content. As someone who has spent 30 years in sales and 20 years watching SEO evolve, seeing this shift to "Answer Engines" is the most significant change I've witnessed.

However, I wanted to share a quick "war story" / observation from the field, especially given the recent news about AI hallucinations (Google's glue on pizza, etc.).

The Observation: I've noticed that even when we get the technical AEO/Schema 100% perfect, the AI models (ChatGPT/Gemini) can still hesitate to recommend a business if the human signals don't match the code.

If we tell the AI via Schema "This is the best specialist," but the reviews/sentiment online are mixed or the NAP data is messy, the AI treats the discrepancy as a "Hallucination Risk" and suppresses the answer to play it safe.

The Solution: "The Trusted Answer System" Because of this, I’ve started adding a pre-work phase before I even touch the schema, which I’m calling The Trusted Answer System.

Basically, I’m spending time manually fixing the client's "Real World" truth (reviews, citations, consistency) first. This ensures that when we do apply the AEO Blueprint strategies, the AI trusts the data immediately because the "Real World" matches the "Code World."

I view it like this: