When it comes to creating content for the web, the Experience, Expertise, Authoritativeness, and Trust (E-E-A-T) framework certainly isn’t new. What is new is how aggressively AI search exposes the difference between real expertise and content that’s just… there. 

In a recent Live Session discussion about AEO strategy between Edgar Allan founder, Mason Poe, and Josh Blyskal from Profound, one idea kept resurfacing in different forms: 

The web is heading toward a separation between people who actually know what they’re talking about, and everyone else.

AI search isn’t creating that divide. It’s just making it impossible to ignore.

AI doesn’t reward “good content.” It rewards credible sources

For years, brands have been told to follow the same rules to ensure good visibility: publish consistently, follow SEO practices, and answer common questions.  A tried and tested strategy in a link-based search world. 

AI search changes the job entirely. 

When an AI model generates an answer, it isn’t ranking pages. It’s choosing which sources to trust enough to speak on its behalf. That’s a much higher bar than “optimized”.

As Josh put it, models are constantly trying to reduce uncertainty. They prefer data sources that sound like they came from someone with lived experience, a clear point of view, and enough confidence to be concise. 

“There’s a flight to quality in web content. People don’t waste time. They don’t suffer model-written content—and they don’t even suffer mediocre content, because it gets lumped in with slop. So people want what real people are saying.”- Josh Blyskal

That’s where E-E-E-A-T stops being theoretical and starts becoming operational.

Why “expertise” is no longer abstract

With traditional SEO, expertise could be implied through:

• Backlinks
• Volume
• Surface-level comprehensiveness

But in AI search, expertise shows up a little differently, such as: 

• Your distinct POV showing up in credible sources
• Specificity over generality
• Language that demonstrates expertise and unique knowledge 

In other words, content that sounds like it was written by someone who’s done the work, not someone summarizing what others have said. 

Josh referred to this as the growing divide between “good actors and bad actors”. Not in a moral sense, but in a practical one: some content meaningfully helps models understand the world, and some content just adds noise. 

“It comes down to the same things good SEOs have been doing: expertise, authority, experience, trust. Plus an understanding of how AIs retrieve info, structure responses, and tokenize answers efficiently.” -Josh Blyskal

AI search is getting increasingly good at telling the difference.

POV is no longer branding. It’s a trust signal.

One of the most important ideas Josh referenced was the emphasis on brand heart–not as a soft concept, but as a structural one. 

“The brand needs to provide a real opinion and perspective. It sounds fluffy, but what matters most is your brand’s heart and your true opinion. You still need a reason for making the content.”-Josh Blyskal

POV isn’t just about what you say. It’s about whether your brand is legible and whether an answer engine can confidently explain you without guessing. Having a clear point of view: 

• Helps humans understand what you stand for. 
• Helps machines understand how to interpret you.

When two sources answer the same question, AI systems are more likely to rely on the one that: 

• Takes a position
• Uses consistent framing
• Demonstrates judgement

That’s why “be the answer” content farms and prompt-gaming approaches collapse so quickly in AI search. They optimize for surface similarity rather than interpretability. 

At Edgar Allan, we don’t see AEO as a content trick. We see it as what happens when brand, narrative clarity, and digital experience are coherent enough to be understood correctly by both machines and people.

Trust is built through systems, not pages

Another theme that came up a lot is the idea that trust isn’t created by a single article or landing page. It’s created by systems. For example, a homepage that says one thing, product pages that say another, and case studies that imply a third create exactly the kind of ambiguity answer engines avoid.

AI models don’t just look at what you say. They infer trust from: 

• Consistency across content.
• How clearly your site communicates intent.
• Whether your experience reinforces your claims. 

Seen through that lens, trust becomes cumulative. It’s not something you “add” to a page, it’s something that emerges when everything a brand puts into the world tells the same story.

This is why AEO can’t live in isolation. 

At Edgar Allan, we treat brand as an operational system that spans:

• Narrative clarity
• SEO foundations
• Conversion logic (CRO)
• Information architecture
• Digital experience design

AEO isn’t a replacement for those disciplines. It’s the outcome when they’re all aligned well enough to be interpreted consistently by both machines and humans.

Where Profound fits into this picture

One of the reasons our conversations with Profound have resonated so strongly is that they’re focused on solving the right problem: visibility, not guesswork.

Their platform gives enterprise teams the ability to: 

• See how their brand actually appears in AI-generated answers.
• Track sentiment and citations across models.
• Understand where they’re being referenced–and what they’re missing.

That matters because you can’t design for interpretation if you can’t see how you’re being interpreted.

Profound isn’t the strategy. It’s the instrumentation. And it allows us to connect AEO back to the things that actually move brands forward: clarity, credibility, and experience.

The separation is already happening

Josh mentioned a likely bifurcation point over the next few years–where content becomes effectively free, and judgment becomes the differentiator. And we’re already seeing early signs of that with AI search amplifying real expertise, clear POVs, and brands that know who they are and why they exist. 

And it’s quietly ignoring everything else. 

That’s not a channel shift, it’s a brand reality check.

Where this leaves teams right now

If there’s one takeaway from our conversations with the Profound team, it’s this: 

AEO isn’t about teaching machines what to say. It’s about making sure your brand is understandable enough to be interpreted correctly; which requires more than just content. It requires coherence. 

If you’re curious about how your brand currently shows up in AI search–whether it’s being cited, summarized, or skipped entirely–contact us to run AEO visibility checks on your brand. Think of it less as an audit, and more as a baseline for how interpretable your brand actually is today.

Read more from the Edgar Allan Blog.

1. Machines Are Reading Your Website (And They’re Probably Getting Your Brand All Wrong)
2. Machines Are Reading Your Website (And They’re Probably Getting Your Brand All Wrong) Part 2
3. From Discovery to Decision: How AEO Changed the CRO Playbook
4. CRO Wins You Can Grab Today All By Your Lonesome
5. Conversations over Clicks: How CRO hits different on B2B Marketing Sites