IN CLEAR FOCUS: Shane H. Tepper, co-founder of AI Friendly, details how generative AI impacts brand discoverability and why now is a “peak ideas person” moment for creative professionals. He outlines the shift from traditional SEO to Generative Engine Optimization (GEO), where AI synthesizes real-time responses. Shane also highlights the importance of adapting content for AI platforms, leveraging third-party validation, and prioritizing continuous relevance for brands in an evolving landscape.
Episode Transcript
Adrian Tennant: Coming up in this episode of IN CLEAR FOCUS.
Shane H. Tepper: Traditional SEO optimizes for algorithms that retrieve and rank existing pages. You’re trying to win a position in a fixed hierarchy. GEO, on the other hand, optimizes for AI systems that generate entirely new responses by synthesizing multiple sources in real time. This is a complete transformation of brand discoverability.
Adrian Tennant: You’re listening to IN CLEAR FOCUS, fresh perspectives on marketing and advertising produced weekly by Bigeye, a strategy-led, full-service creative agency growing brands for clients globally. Hello, I’m your host, Adrian Tennant, Bigeye’s Chief Strategy Officer. Thank you for joining us. We’re living through what may be the most significant shift in how consumers discover brands since the advent of the internet. Generative AI platforms such as ChatGPT, Perplexity, and Google’s AI Overviews are fundamentally changing how people search for information. Instead of clicking through search results, consumers are increasingly getting direct answers from AI models. This shift from traditional SEO to what experts call Generative Engine Optimization, or GEO, presents both opportunities and risks for brands. Our guest today is at the forefront of these changes. Shane H. Tepper is a creative director, content strategist, and co-founder and CEO of AI Friendly, a company that helps brands optimize their visibility across AI platforms. Based in Atlanta, he has over 15 years of experience in brand storytelling and has authored foundational white papers on GEO strategy. Shane is also the author of Dwelling in a Place of Yes, the surprising psychology behind fear, opportunity, and smarter choices. And most provocatively, he’s written about what he calls the peak ideas person moment, a brief window where human creativity may be at its highest economic value just before AI potentially surpasses it. To discuss how brands can navigate AI transformation and what it means for the future of marketing, I’m delighted that Shane is joining us today from Atlanta, Georgia. Shane, welcome to IN CLEAR FOCUS.
Shane H. Tepper: Delightful to be here, Adrian. Thank you for having me.
Adrian Tennant: Well, Shane, you’ve written that we’re living in a unique moment where human ideas are more valuable than ever, but that this window is closing. Can you explain your thesis?
Shane H. Tepper: Certainly. So I had this moment back in early 2023. I was in my apartment in San Francisco. I had just been laid off from my copywriter job. I was packing up my life, preparing to move back home to Atlanta. And I came across the first release of ChatGPT. And I had a creative brief from my previous job. And this creative brief described a project and the copy would typically take me about 45 minutes to produce based on the parameters of this brief. I fed it into ChatGPT, and it churned out clean, dare I say, eloquent copy in seconds that required minimal revisions. And that’s when I started having these thoughts about how we’ve reached something that I refer to as peak ideas person. For decades, ideas were cheap and execution was expensive. The quote-unquote ideas guy was dismissed because you needed specialized knowledge, resources, connections to build anything real. And then suddenly, with the emergence of LLMs, this equation had flipped. Right now, if you can generate valuable ideas and orchestrate AI tools, you have exponential leverage. I can build a functional app prototype in hours with just my words. It’s called vibe coding. You just use written prompts, and you can create a functional prototype of a web application. It’s incredible. You can write content at scales that were previously impossible. This is a fundamental transformation of how work gets done. But the uncomfortable reality is this, AI’s ideation capabilities are improving exponentially. The training data now includes entire creative processes, how to develop ideas, iterate on those ideas, fail, and evolve. And we’re seeing emergent behaviors in these models that resemble genuine creative thinking. So the timeline for when AI matches human ideation capability isn’t decades long. We’re talking years long. Now, whether that’s two years, three years, five, seven, it’s unclear. But when that happens, when AI achieves parity with human creative thought, this brief period of peak ideas person, I think, will be over. And with it, potentially the last clear economic advantage that humans possess over machines. This window of opportunity is closing and quickly. And the question is, what do we do with that knowledge while we still can’t, while we still have inherent economic value as human beings?
Adrian Tennant: You’ve been tracking the shift from traditional search engine optimization to generative engine optimization or GEO. For marketers familiar with optimizing for Google search, how does optimizing for AI platforms differ fundamentally?
Shane H. Tepper: So most marketers think that GEO is SEO for AI platforms. And that is a helpful little heuristic to understand fundamentally what it is. But that’s also similar to saying a Tesla is a horse but with wheels. So traditional SEO optimizes for algorithms that retrieve and rank existing pages. You’re trying to win a position in a fixed hierarchy. GEO, on the other hand, optimizes for AI systems that generate entirely new responses by synthesizing multiple sources in real time. So I saw a piece of research recently that said that AI mode indexes passages instead of pages. So each passage embedded within a page in a vector space is evaluated. The competition isn’t among websites, but more among chunks of content. So think about what that means. In SEO, you’re optimizing for pages. In GEO, you’re optimizing for thoughts. So every paragraph needs to be a complete self-contained idea that can stand alone when an AI system pulls it into a response. So the rules aren’t just different, they’re inverted. Your SEO optimized content could be completely invisible on AI platforms. So this is more than an evolution, I think. This is a complete transformation of brand discoverability.
Adrian Tennant: In your white paper, which you published on Medium, you found that there’s often less than 10% to 12% overlap between websites that rank highly on Google and those cited by AI models. Shane, what does this mean for brands that have already invested very heavily in traditional SEO?
Shane H. Tepper: I think it means that your SEO success provides a false sense of security now that we’re in the AI era. You can be dominating Google while being completely invisible when your highest intent buyers are actually looking for you on an LLM. I’ve watched companies, you know, pat themselves on the back for their number one ranking on Google while their competitors are shaping the entire narrative in AI responses. And the brutal truth is that 90% of chat GBT citations come from pages ranking 21 or higher in traditional search. So AI platforms aren’t just ignoring your top content, they’re actively preferring what SEO would consider to be failures. For brands that have invested thousands or more in SEO, this isn’t necessarily money down the drain, but it’s definitely not portable value. You can’t take that and shift it over to LLMs. Your content might be good, but it’s structured for the wrong game. Your keyword research is no longer valid when it comes to LLM discoverability. Your link-building strategy is irrelevant. So the companies that are winning right now are the ones that are building authority on Wikipedia. They’re the ones that are engaged authentically in conversations and communities on Reddit. They’ve created educational content that people actually cite, not because they’re gaming AI, but because they’re focused on providing genuine value rather than trying to optimize for Google’s algorithm. The irony of the entire situation is that the best practices that made you successful in SEO might actually be what’s making you invisible in AI.
Adrian Tennant: Shane, you’ve studied how different AI platforms, such as ChatGPT, Perplexity, and Google AI Overviews, each have distinct citation preferences. Can you walk us through some of those differences and what they mean for content strategy?
Shane H. Tepper: This is a particularly interesting question because here’s what I thought I knew. I thought I knew that ChatGPT loves Wikipedia. I thought I knew that Perplexity runs on Reddit, that Google AI overviews creates listicles. These seem to be clean patterns with predictable strategies to apply. And then I saw some research recently that indicated that over 50% of AI citations change in just a single month. Google AI overviews, for example, 59.3% new domains. ChatGPT, 54.1%. Perplexity, which seemed the most stable, still churned at over 40%. So that is chaos. So the platform preferences I’ve been tracking, Wikipedia for ChatGPT, Reddit for Perplexity, those are real, but they’re snapshots. They’re not permanent rules. So, what this actually means for content strategy is a bit more unsettling than what I originally thought. You can’t just create the perfect Wikipedia entry and coast on ChatGPT’s visibility. You can’t build a Reddit presence and assume perplexity will keep citing you. Authority in AI search isn’t cumulative like SEO. This is a fundamental difference between GEO and SEO. It’s contextual, it’s temporal, and it’s very competitive. Freshness beats domain history. Relevance beats authority. Structure beats legacy content. So the real strategy isn’t necessarily different approaches for different platforms. It’s building content systems that can adapt in real time. It’s understanding that what works today might be invisible tomorrow and planning for that volatility rather than pretending it doesn’t exist. And the thing is, most brands are still thinking in SEO terms. Build it once, optimize it, and occasionally maintain your rankings. But AI search rewards the constantly relevant, not the historically dominant. So the question isn’t just how do I get cited? It’s how do I stay cited when the citation landscape is changing so frequently?
Adrian Tennant: Okay, well let’s get practical. How should brands think about creating content that can perform across these different AI platforms?
Shane H. Tepper: So fundamentally, marketers need to think like AI systems trying to understand and sell your content, not like marketers trying to rank for keywords. What I have is an agentic process that I refer to as a translation layer. So I stop writing in marketing language and start writing in customer language. Instead of best-in-class revenue attribution solution, for instance, it’s figure out which marketing actually drives deals. AI systems understand the context and the intent, not your buzzword density. Then what you do is you optimize at the passage level. Every paragraph needs to be a complete thought that could be lifted out and cited independently. You know, no more as mentioned above or the solution described below each section needs to stand alone. And I don’t want to discount altogether SEO best practices because the technical stuff is still important. The semantic HTML, proper schema, but the foundation is always authentic. language that people are actually using when they search in these LLMs with actual language that they’re including in their queries. And you need to structure this content again for comprehension and not keywords. So the key insight here, I think, is that AI platforms are looking for truth, not optimization. They want to cite content that makes them look smart and helpful. And you want to be that content.
Adrian Tennant: One of the most striking findings in your research is that visibility in AI responses isn’t earned once, it’s rebuilt every time someone asks a question. Shane, how does this change how brands should think about their digital presence?
Shane H. Tepper: Third-party validation, content that exists independently of your own website, plays a crucial role. AI platforms essentially outsource credibility assessment to community validators. So when ChatGPT cites Wikipedia or Perplexity references a Reddit discussion, they’re leveraging collective intelligence rather than trying to assess the authority themselves. It’s pretty brilliant, actually, that they’re systematizing how humans naturally evaluate credibility. So think about it. You trust peer reviews more than corporate websites, right? If someone is telling you that, hey, I use this product or I engage with this brand, and it provided value to me. That is much more powerful than going to a brand’s website and reading some passage about them beating their chest about what an awesome solution they are. So you value these sorts of community discussions over press releases. You believe Wikipedia more than company about pages. AI platforms have automated this human instinct. And this is why having an updated Wikipedia presence isn’t like a nice-to-have feature for visibility in these platforms. It’s mandatory. Why authentic Reddit engagement drives perplexity citations. Why G2 reviews have become critical for B2B SaaS visibility. The brands winning right now understand that their reputation across AI systems isn’t built on their own properties. It’s built on what everyone else says about them in places AI systems trust.
Adrian Tennant: Got it. Let’s take a short break. We’ll be right back after this message.
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Drawing on nearly thirty years of experience working with brands such as Disney, Marks & Spencer, and American Express, I reveal how emotions, perceptions, and social factors influence consumer behavior in our evolving retail landscape. This book provides practical insights into everything from the psychology of pricing to creating immersive retail experiences that resonate with customers. You’ll discover real-world examples from leading companies and learn how to blend physical and digital elements to create memorable, value-driven shopping experiences. As an IN CLEAR FOCUS listener, you can save 25% on The Science of Shopping when you order directly from KoganPage.com. Just enter the exclusive promo code BIGEYE25 at checkout. Shipping is always complimentary for customers in the US and UK. I really hope my book helps you understand what motivates us as shoppers and how to develop effective retail strategies. Thank you! |
Adrian Tennant: Welcome back. I’m talking with Shane H. Tepper, the co-founder and CEO of AI Friendly, a company that helps brands optimize their visibility across AI platforms. When we were preparing for this podcast, you mentioned that you’re seeing the emergence of conversational search, that is longer, more natural language queries. How should brands optimize their content for this shift in search behavior?
Shane H. Tepper: Yeah. So there’s fascinating research that has been done by MIT that shows that our brains construct hierarchical sentence structures rather than process individual words. So this explains why conversational queries feel more natural. They mirror how people actually think. It’s a dramatic shift. Traditional SEO thinking is enterprise CRM software. How people actually search AI would be something like, what’s the best CRM for a 500-person company that needs to integrate with Salesforce and has a remote sales team? Much more long-tailed, much more context, much more specific to a particular use case. So the average chat GPT query is packed with context, intent, and specificity. People have learned to communicate with AI systems the way they communicate with intelligent human beings, in complete thoughts, not in these sort of fragmented keywords. So to optimize for this, you need to do what I have been referring to as customer voice archaeology. You mine your sales calls, your support tickets, your customer emails, and you find the exact words that people use when they describe their problems, not how you describe your solutions in marketing speak. And then what you do is you structure content to answer complete questions, not match keywords. So that involves creating FAQ sections that mirror this natural language that people are using. You write like your customer talks, not like your marketing team thinks.
Adrian Tennant: You’ve co-founded a GEO platform that goes beyond metrics and insights to provide specific optimization recommendations. Can you tell us more about it?
Shane H. Tepper: Certainly. I’m the co-founder of a company called AI Friendly, and we help brands optimize their visibility across LLM platforms where high-intent buyers are comparing brands and making purchasing decisions, sometimes within a single conversation. And as you alluded to, we go beyond just showing metrics or insights. Metrics and insights, like what platforms you’re appearing on and what the citation sources are for those platforms. Competitive analysis, like how are you comparing against your top competitors. Sentiment analysis. Concerning whether people are talking about your brand favorably, neutrally, or in a negative way. These are all valuable, but that value is lost when you don’t take those learnings and apply them in some sort of a strategic way to improve your visibility on these platforms.
Adrian Tennant: For brand marketers listening to our conversation, what are the first steps they should take to audit their current visibility in AI generated responses?
Shane H. Tepper: So here’s how I would approach that. Take 20 to 30 queries that represent how your customers actually search for solutions, not your brand name, exclude your brand name, but specifically the problems that you solve. So unbranded queries that should result in your brand being surfaced in an AI response. So test them across LLMs, ChatGPT, Perplexity, Claude, Gemini. Document everything, where you’re appearing, how you’re described, in what context are you being cited, and more importantly, document where you should appear but don’t. Look for these three critical gaps. Accuracy gaps, where you’re mentioned but incorrectly described. Visibility gaps, where competitors appear but you’re invisible. And authority gaps, where you have expertise but no recognition in citation sources. Then audit your third party presence, check Wikipedia, check industry review sites, check community discussions about your space in different forums. These matter more than your website for AI visibility. And the goal is to understand your baseline so you can measure improvement. And I think most brands will be shocked by how invisible they are.
Adrian Tennant: And this is something AI Friendly can help with?
Shane H. Tepper: This is absolutely something AI Friendly can help you with! We take a look at your discoverability status across all of these factors that affect your discoverability and then provide strategic recommendations on how to create and deploy content to improve your discoverability in those key LLM platforms.
Adrian Tennant: Perfect. Shane, your book, “Dwelling in a Place of Yes,” explores decision-making during uncertain times. How does this philosophy apply to brands trying to navigate the AI transformation we’re discussing?
Shane H. Tepper: Yeah, so the core premise of dwelling in a place of the S is that uncertainty isn’t a problem to solve, but rather it’s the environment where opportunity lives. So most brands become paralyzed waiting for perfect information about AI that will never come because of some of the things that we’ve previously discussed, the high rate of churn. It’s difficult to hit a moving target. And that’s exactly what optimization is for AI. It’s not something like SEO where you structure your website properly and you’re instantly more discoverable. This is an ongoing thing. So I think a lot of brands are asking the wrong questions. Should we invest in GEO, in generative engine optimization? What’s the ROI for it? What if the platforms change? I think the questions that they should be asking are more along the lines of, What can we learn about how our customers naturally express their needs? How can we create more helpful content to address those needs? Where can we add authentic value to community discussions? Because you can’t control whether AI platforms change their algorithms and they are constantly changing, but you can control whether you understand your customers deeply. You can’t predict the future of search, although we are seeing a massive shift from traditional search like Google toward these LLMs, especially for high-intent buyers, but you can create content that provides genuine value regardless of the platform. So it seems to me that the brands that will thrive will be those comfortable with intelligent experimentation rather than those who are demanding guarantees, because there are no guarantees. And they fundamentally understand that in this sort of uncertain environment, the biggest risk of all is taking no risk.
Adrian Tennant: For your book, in what kinds of ways did you use AI during the research and writing process?
Shane H. Tepper: In so many ways, AI was my research partner, it was my intellectual sparring partner, and it was my co-author. For research, I used AI to pull in sources that described a lot of the psychological concepts that I was exploring. pulling sources from valid studies, credible studies, credible people in psychology, in sociology, in anthropology, to sort of undergird the assertions I was making. I wanted the book to be backed by hard science, by research, for credibility reasons. I didn’t want to write a fluffy book. I wanted to write something that was highly credible and well-sourced. I had a number of anecdotes from my own life and career that sort of provided the infrastructure for the book on which I could layer these additional insights and sort of build a framework around the decision-making process and how humans naturally tend to adopt this sort of no mindset. And there are powerful psychological reasons why we sort of default to no. But, and this may seem obvious, you are at a much greater advantage when you approach a situation with what I have termed strategic openness. This isn’t blindly saying yes to any opportunity that comes your way, but it’s having a methodology for evaluating that opportunity on a number of levels and then making a very informed decision on whether to say yes or not.
Adrian Tennant: Shane, how do you recommend balancing AI automation with maintaining a personal touch in customer interactions?
Shane H. Tepper: That’s a really interesting question, because people don’t want to feel like they’re interacting with a machine. They want a natural-feeling interaction with a brand. So I think the balance is this. You automate the intelligence and you humanize the response. AI is phenomenal at servicing signals like which sources a platform is citing, which prompts are trending, and how your brand is being portrayed in those responses. But it takes a human to translate those signals into strategy. So here’s how we approach it. We use AI to spot where the attention is going. So for instance, we might see that perplexity is citing Reddit threads 45% of the time in a given category. And this tells us that the audience values peer voices and community dialogue, but you want to respond with authentic human input. So that’s when we’ll advise a client, hey, let’s have your head of product or your top customer sales representative answering the right questions in those threads and let’s do it today. because as we described earlier, timeliness is critical. So to summarize, AI shows you the map, but it’s up to the human to stay alert at the wheel, so to speak. This isn’t about AI replacing the human touch, but rather about using AI to amplify the right human touch in the right place at the right time.
Adrian Tennant: We’ve discussed the challenges AI presents extensively. What excites you most about the opportunities it creates for creative professionals and marketers?
Shane H. Tepper: This is a great way to come full circle and address the peak ideas, concepts that we explored earlier in our conversation. For the first time in decades, strategic thinking matters more than executional capability. The person who can see around corners and orchestrate complex solutions has more leverage now than the person who can just perform tasks at a really high level. I can now test creative approaches that would have required entire teams and iterate in real time. I can analyze performance patterns at scales that were impossible before. I can move from concept to market faster than ever. Essentially, the distance between an idea and its successful execution has been dramatically collapsed. But I think what really excites me is the problem-solving potential. When execution becomes frictionless, like it has, you can tackle challenges that were previously too resource-intensive. You can create personalized experiences for market segments of one. You know, you can target individuals. You can test innovative approaches without, you know, putting your company financially at risk. So for creative professionals who learn to orchestrate in this way rather than compete with AI, the opportunities are unprecedented. But the caveat again is that this window will not last forever. In fact, quite the opposite. It’s rapidly closing. AI is rapidly developing ideational capabilities that will eventually, I feel confident in saying this, make human creativity substantially less valuable. But those who embrace this moment we’re in right now, who learn to dance with AI rather than fight it, I think the next few years could be some of the most creatively fulfilling of our careers. So the question then becomes whether you’ll spend this time building or hiding.
Adrian Tennant: Great conversation. If listeners would like to learn more about AI-Friendly, what’s the best way to connect with you?
Shane H. Tepper: You can go to getaifriendly.com. That is G-E-T A-I F-R-I-E-N-D-L-Y .com. You can read all about what we’re doing, and you can get in touch with us via the website as well.
Adrian Tennant: Shane, thank you very much for being our guest this week on IN CLEAR FOCUS.
Shane H. Tepper: It was an absolute pleasure, Adrian. Thank you again.
Adrian Tennant: Thanks again to my guest this week, Shane H. Tepper, the co-founder and CEO of AI Friendly, a company that helps brands optimize their visibility across AI platforms. As always, you’ll find a complete transcript of our conversation with timestamps and links to the resources we discussed on the IN CLEAR FOCUS page at Bigeyeagency.com, just select ‘Insights’ from the menu. Thank you for listening to IN CLEAR FOCUS, produced by Bigeye. I’ve been your host, Adrian Tennant. Until next week, goodbye.
TIMESTAMPS
00:00: Introduction to Generative Engine Optimization (GEO)
02:30: The Peak Ideas Person Moment
05:18: Differences Between SEO and GEO
07:15: The False Security of Traditional SEO
09:08: AI Platforms and Citation Preferences
10:56: Content Strategy for AI Platforms
13:16: The Importance of Third-Party Validation
16:05: Conversational Search and Natural Language Queries
18:22: Introducing AI Friendly
19:28: Auditing Current Visibility in AI Responses
20:49: Navigating Uncertainty in AI Transformation
23:28: Using AI in Research and Writing
25:05: Balancing AI Automation with Human Touch
26:41: Opportunities for Creative Professionals
28:47: Connecting with AI Friendly
