AI-Adaptive SEO: The Future of Organic Visibility Including AI Search
Season: 2 | Episode: 40
Published: October 27, 2025
By: Byer Co
This episode is based on an article by Jeff Byer, CEO of Byer Company, detailing the necessary evolution of search engine optimization (SEO) into what he terms AI-Adaptive SEO. Byer asserts that the rise of conversational AI search fundamentally changes how people find information, requiring a shift from traditional keyword-focused strategies to new methods. The article emphasizes that while the foundational principles of SEO—such as user intent, E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness), and technical site health -remain essential, new strategies must be adopted. These modern approaches include optimizing content for topical authority rather than specific keywords, structuring material to be "cite-worthy" by AI overviews, and using advanced schema markup to guide machine understanding. Ultimately, the source functions as a guide, urging businesses to update their content creation and technical structure to secure organic visibility in the new AI-driven search landscape.
Link: AI-Adaptive SEO: The Future of Organic Visibility Including AI Search
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Episode Transcript
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Welcome back to Digital Rage. I am Jeff, the producer here at Byer Company.
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In this episode we are talking about AI Adaptive SEO. This is my article in
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reaction to a lot of clickbait articles claiming that everything you know
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about SEO is obsolete. The fundamentals of SEO are still very relevant. Even
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required in order to surface an AI response. Let's dig in.
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Welcome to The Deep Dive. We're here to cut through the noise and give you the
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concentrated knowledge you need. And today we're tackling something big.
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Sources are pretty much unanimous. This is the biggest shakeup in SEO we've
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seen in what 20 years. Oh easily. It's absolutely seismic. This isn't just
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you know, tweak in your H1 tags or chasing another algorithm update. We're seeing
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a fundamental change in how people actually find information online. Right.
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It's that shift away from just keywords. Exactly. Towards more complex
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conversational questions that you ask an AI. So our mission today is to unpack this
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move from the SEO we all knew focused on getting that number one ranking to what
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people are now calling AI Adaptive SEO. We've got a lot of analysis here and it
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all boils down to one core question really. Which is if the goal isn't hitting
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number one anymore but instead becoming the trusted authoritative source that an
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AI actually sites in its answer. Well what do you as a content creator need to do
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differently like starting right now. That's the million dollar question isn't it
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that difference ranking versus being the cited source that's the absolute heart
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of this new way of thinking. Okay. But before anyone panics and throws out
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everything they've learned we really need to stress that the old foundation is
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still crucial. So the traditional playbook isn't dead. Not at all. Think of it
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more like the the price of admission now. It gets you in the game. Okay let's nail
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down those ground rules then. What are the non-negotiables? The things that
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you know even allow an AI to consider your content. Well it still starts and
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honestly probably still ends with user intent. AI models are getting incredibly
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good at understanding not just the words someone types but what they actually
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want to achieve. The underlying goal. Precisely. If your content doesn't nail
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that doesn't fully satisfy what the user is trying to do solve their problem.
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The AI is just going to look elsewhere and 10 is still king. Absolutely. And the
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filter the AI uses for quality. That brings us back to EET right? Experience,
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expertise, authoritativeness, trustworthiness. Our listeners know the acronym but
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how does AI change its importance? Why does it matter more now? Ah because EET
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has essentially become the AI's primary safety mechanism. Think about it.
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These large language models the systems using RI retrieve a logmented
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generation they're designed to prioritize established authority to avoid
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mistakes. Exactly. They get penalized for making things up for hallucinations or
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just spitting out low quality info. So to reduce that risk they actively hunt for
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content that demonstrates real verifiable experience and deep expertise. So it's
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more than just having a decent about us page now. It sounds like the AI is
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actively checking cross referencing your credentials maybe your site's history
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against what it already knows. That's exactly right. It's not just taking your word
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for it. It's looking at your track record. Who links to you? Who sites you? The
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overall quality and focus of your site. It's deciding if you're genuinely trustworthy.
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Established proven authority gets cited. Thin, anonymous or low quality stuff.
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That's a liability for the AI. It just gets ignored. That's a really key point.
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Okay what about the technical side? Technical SEO often feels like the the less
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glamorous part. Yeah. But the source is insist it's a baseline non-negotiable. If
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my content and EET are solid why do I still need to obsess over core web
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vigals or site structure? Doesn't the AI just read the text? It cares about
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efficiency. I mean think about the sheer scale of data these models process.
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Technical SEO especially speed, crawlability, clean architecture. It's essential
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for the AI bots to even access and process your content efficiently. So if my site
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slow or messy? The bot just moves on. Why would it waste computing power trying to
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untangle a slow confusing site when there are thousands of other authoritative
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sites that are technically perfect? It's a prerequisite now. Technical
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excellence gets you seen. Okay foundation established authority verified
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intent satisfied sites fast. Now let's dig into the big strategic pivot. This is
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where it gets really interesting moving from that old goal. Number one rank
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maybe the featured snippet to what we're calling the site worthy content
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strategy. The new game is creating a resource that's so definitive, so well
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structured that when the AI builds its answer for a user it chooses your
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content as the reference link. It points back to you, which means rethinking how
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we approach topics right moving beyond just clusters of keywords.
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Absolutely. We have to optimize for entire concepts now building real
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topical authority. Explain that a bit more. The old way was. The old way was
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often spray and pray right 10 slightly different articles to catch 10
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slightly different keyword variations. Right. But AI doesn't just match
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keywords anymore. It understands the deeper connections, the semantics
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between all the ideas within a whole topic. So the new approach is one
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definitive guide. Pretty much. Instead of 10 thin pieces you build one
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comprehensive pillar style resource. Something that covers the core topic from
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well every angle. You proactively answer the main questions, the follow up
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questions, the what ifs. And that signals reliability to the AI.
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It signals completeness. These RRAG system are designed to synthesize
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information. If you provide the most complete reliable picture in one place,
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you stop being just a collection of keyword targeted pages and you start
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becoming a true authority on the subject. Okay, I get the authority angle.
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But let me push back slightly. If I create one monster guide, won't that page be huge?
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Potentially slow. Doesn't that hurt my core web vitals? The very thing we just said
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was crucial. That's a fair point. And it's where structure becomes
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absolutely paramount. You can't just dump 10,000 words onto a page. You need smart
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structure like using internal jump links, clear headings, maybe concise
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summaries at the top. Really clean code is essential too. And remember,
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topical authority isn't just about length. It's about completeness and value.
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Every section has to deliver. So depth is good, but it has to be well organized
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and fast. Exactly. The AI is sophisticated. It can appreciate the depth.
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But only if the technical side, the delivery mechanism is smooth and fast.
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Right. Makes sense. Okay, so that brings us to the real nuts and bolts.
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If the goal is to be site worthy, what are the practical steps?
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The mechanics of structuring content so an AI can easily almost automatically pull
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information out and attribute it correctly. We're talking machine efficiency here.
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You've nailed it. That's the philosophical shift. You're essentially building a reference
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document specifically for an AI model. Meaning, meaning your content needs
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clear factual statements. Things that are easy to verify.
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The machine doesn't want to wade through paragraphs of flowery prose to find one simple data point.
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It wants the facts cleanly presented. And what specific structures make that happen?
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Make extraction easy. This is where specific formatting tools become critical.
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We're talking about leveraging things like bullet points, numbered lists,
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detailed comparison tables and really clear definition. Job, why those specifically?
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Because they're formatting gold for an AI. They are super easy to parse, easy to extract,
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specific pieces of information from. And this is key, easy for the AI to attribute back to you
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accurately. So if you can pull a perfect quote from a bullet point or a table cell.
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The risk of it misinterpreting or hallucinating drops significantly, which makes the AI much more
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likely to choose your content to cite. So simplifying complex ideas into say a bulleted list
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isn't just for human readers anymore. It's a strategic choice for the AI.
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It absolutely is. And tied into that is building what some call the web of trust.
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It's not just about presenting data. You need to cite your own sources within your content.
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Show the machine your homework. Demonstrating rigor. Exactly. That internal rigor signals the AI
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that your information is well researched, verified, reliable. It just builds confidence.
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It makes the AI more comfortable using you as a primary reference.
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Makes sense. Make it easy to cite. Make it trustworthy to cite.
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And I can see how this connects to how search feels more conversational now.
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You ask one question. You usually have follow-ups in mind.
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Precisely. AI search tries to anticipate that next step.
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Think about the people also ask box in Google search results.
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That's a basic version of this conversational flow.
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So that box is actually a gold mine. It's a gold mine for understanding the PAS users take.
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Your content needs to do the same thing. Answer the main question, sure.
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But then proactively answer those likely secondary tertiary follow-up questions.
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If you do that, you become the go-to source the AI keeps coming back to within that single user
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session. We've covered content structure, citing sources. Now let's talk about guiding the
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machine more explicitly. The source material really hammers home that schema markup has gone from,
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like a nice to have bonus to a critical requirement for this AI adaptive SEL.
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Why such a big jump in importance.
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Okay, think of schema as like the detailed nutritional label on your food packaging,
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but for your content. The AI bot doesn't want to guess what it's looking at.
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It wants the facts up front. Exactly.
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schema gives the bot a guided tour. You're explicitly telling it.
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This section here is a definition. This part is a step-by-step how-to guide.
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Here are the authors credentials. These are FAQs.
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So simply using the basic article schema isn't really cutting it anymore. We need to get more
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specific. You absolutely must. Basic article schema just says, "This is an article." Okay, fine.
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But detailed schema like FAQ page schema. That gives the AI the exact question and answer
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pairs it needs for clean attribution. How-to schema structures the steps perfectly?
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It takes the guesswork out. Completely. It removes ambiguity for the AI.
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It guarantees the machine understands the purpose and structure of your information,
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which dramatically boosts your chances of being selected and cited correctly,
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especially for those structured answers AI often generates.
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The message seems loud and clear. If you don't explicitly label your content for the AI,
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it might not know how to use it properly or it might just skip it.
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Okay, this has been a really solid framework for everyone listening,
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nodding along, thinking about their own site. What are, say, the top three actionable things they
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should prioritize, like this week. Okay, three things. First, conduct a real topical authority audit.
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Pick your main subject areas, maybe your top three. Map out all your existing content against those
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topics. Where are the gaps? Yes, in terms of gaps in covering those secondary and tertiary
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questions. Maybe you've covered the what is X really well, but you completely missed the,
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how do I use X or the why should I care about X compared to why? Find those gaps and fill them
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aim for completeness. Got it. Step one, audit for completeness. What's number two?
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Number two, optimize your existing high performers for site worthiness. Look at the pages that
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already get traffic that already rank reasonably well. Go into those pages specifically looking for
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opportunity. Like taking a dense paragraph, explaining a concept and breaking the key takeaways into
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a bulleted list or finding comparisons and putting them into a simple table, adding specific
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data points with sources basically make it incredibly easy for an AI to grab a perfect self-contained,
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a attributable quote. Effortless extraction. That seems to be the mantra. Okay, and the third action
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item. What about new content? For new content, target explanation queries. Really focus your creation
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efforts on those in-depth conversational answers. The how, the why, the what is type questions. Why
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those specifically? Because that's where AI often shines providing detailed explanations. If you
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can create the most comprehensive, the most verifiable, the best structured explanation for those core
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informational queries, you position yourself as the go-to reference source that the AI will naturally
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gravitate towards. Commercial content will evolve sure, but the need for clear authoritative explanations
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isn't going away. It really sounds like this AI adaptive approach isn't some passing fad. It's
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the next chapter for SEO, isn't it? And taking your solid traditional SEO foundation and layering
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on this focus on, well, citation mechanics, that seems like the key to getting ahead right now.
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Absolutely. It's about understanding how the machine works, its constraints, its priorities,
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like avoiding errors and citing reliably, and then building your content to meet those needs,
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be the best, most verifiable, and crucially the most easily attributable answer out there.
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So let's zoom out for a final thought. What does all this really mean? If these AI systems are
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fundamentally designed to reward EAT, to reward clear structure, to reward meticulous sourcing.
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Does becoming AI adaptive essentially mean we're being pushed back towards a higher standard,
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maybe even more like academic rigor, but for all online content? Is the machine, ironically,
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forcing us all to be better researchers and clearer writers? Something for you to think about is
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you start auditing your own topics. Thanks for joining us for this deep dive.
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Reach out to us at jbuyer.com for comments and questions. Follow us at buyer company on social media,
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and if you'd be so kind, please rate and review us in your podcast app.