Found in AI: AI Search Visibility, SEO, & GEO

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Are marketers so focused on optimizing content for AI search engines that they're forgetting to create content people actually want to read? In this episode of Found in AI , Cassie Clark welcomes Holly Enneking, VP of Marketing at Markup AI (formerly Acrolinx), to discuss how brands can balance AI search optimization with content quality, original perspectives, and a consistent brand identity. Holly shares what her team has learned while transitioning a 20-year-old brand to a new identity, including how they're evaluating existing content, updating high-performing pages, and working to establish Markup AI's presence across traditional and AI search engines. The conversation also covers Markup AI's early results, including a reported 30%+ increase in blog engagement over six months, stronger engagement from third-party content distribution, and gradual improvements in AI visibility. In This Episode Why writing for humans still matters in AI search optimization How to balance GEO best practices with original insights and brand voice What happens to AI search visibility when a company rebrands How Markup AI is transitioning from Acrolinx while preserving valuable existing content How to decide which older articles to update, migrate, or retire The role of content structure, FAQs, metadata, and consistent brand messaging How to evaluate content engagement alongside AI search visibility metrics One Thing to Try This Week Choose five important pages from your website and ask: Does this content still serve the audience we're trying to reach? Does it offer something readers can't find on a dozen competing websites? Does it accurately represent our brand and what we do today? You may find that your next AI search content opportunity isn't a new article. It's improving something you've already published. More from Cassie Clark Marketing Need help with your AI search visibility strategy? Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. Explore AI search visibility audits, content strategy, and team training at Cassie Clark Marketing . Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe What happens after AI search recommends your brand? Does someone click through to your website? Can an AI agent purchase your product? And can you actually measure the traffic you're getting? In this October 22 Found in AI news update, Cassie Clark looks at three developments that show where AI search is heading beyond brand mentions and citations. Google is making source links more visible in AI Overviews and AI Mode, but a big question remains: will those changes increase website traffic? Walmart has launched Agent Gateway, giving approved AI agents a way to shop and complete purchases. And OpenAI has fixed the ChatGPT UTM tracking bug that caused referral traffic to disappear from analytics earlier this month. Well, mostly. In This Episode Google's AI search updates: Why Google is moving source links higher in AI-generated answers, what the growth of Preferred Sources tells us about brand trust, and why we still need click-through data. Walmart's Agent Gateway: How Walmart is opening its shopping infrastructure to approved AI agents, why its approach differs from Amazon's, and what this means for agentic commerce. ChatGPT's tracking bug: What happened to ChatGPT referral traffic between October 8 and 15, why visits were showing up as Direct traffic in GA4, and what marketers should check in their October reporting. The bigger takeaway? AI search visibility is only part of the picture. Brands also need to consider what happens after a recommendation, whether that's a website visit, a purchase, or another action that drives business results. More from Cassie Clark Marketing Need help with your AI search visibility strategy? Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. Explore AI search visibility audits, content strategy, and team training at Cassie Clark Marketing . --- Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe The traditional marketing funnel no longer reflects how people discover brands. Buyers are turning to AI search engines, social media, podcasts, and trusted voices to research their options. So what does that mean for marketers? In this episode of Found in AI , Cassie Clark welcomes Caitlin Milliken-Flohr from HubSpot to discuss Loop Marketing , a new framework designed around how buyers discover and engage with brands today. Caitlin breaks down the four stages of Loop Marketing — Express, Tailor, Amplify, and Evolve — and explains how marketers can use AI to better understand their audiences, scale content without losing their brand identity, and reach buyers across different channels. They also explore how smaller teams can build visibility without enormous budgets, why internal thought leaders are an overlooked marketing asset, and how shorter experiments can help teams learn what's working before committing more resources. In this episode Why HubSpot introduced Loop Marketing The four stages: Express, Tailor, Amplify, and Evolve Maintaining brand identity while scaling content with AI Using customer insights to personalize marketing Where AEO and AI search visibility fit into a broader strategy Building brand authority through employees and thought leadership Testing marketing ideas with shorter sprints and measurable KPIs More from Cassie Clark Marketing Need help with your AI search visibility strategy? Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. Explore AI search visibility audits, content strategy, and team training at Cassie Clark Marketing . Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/ Wondering what AI search means for your business? Cassie Clark Marketing helps startups and enterprise brands understand how AI systems discover and recommend them, identify what affects their visibility, and develop executable strategies. Services include team training, AI visibility diagnosis, strategic consulting, and fractional marketing leadership. www.cassieclarkmarketing.com

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI , Cassie Clark talks with Peter Rota, an SEO professional with 15 years of experience, about the rapidly growing market for AI visibility tools — and where those platforms still have room to improve. Cassie and Peter discuss why actionability remains one of the biggest challenges with AI visibility software, what teams should look for when evaluating a platform, and why a visibility score alone may not tell you very much. They also dig into one of the biggest AI search measurement questions: should brands care more about being cited, mentioned, or actually recommended? Peter shares his own hierarchy — recommendation, mention, then citation — and explains why citations can sometimes come dangerously close to becoming a vanity metric if they aren't connected to meaningful business outcomes. In this episode: Where AI visibility tools are useful — and where they still fall short Why AI visibility data needs to lead to action What to consider before paying for an expensive AI visibility platform Why prompt-based visibility scores don't tell the whole story Why mentions and citations shouldn't be combined into one metric The difference between being recommended, mentioned, and cited When citations risk becoming a vanity metric Why the intent behind the prompt matters How to identify a perception gap between your website and an AI system's understanding of your brand Why lower-funnel prompts may be more valuable to track Whether your next AI search investment should be software or a person who can actually turn the data into strategy -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Ryan Doser has been working in SEO for roughly a decade. But as search behavior has expanded beyond Google into ChatGPT, YouTube, TikTok, Reddit, and other platforms, he's started thinking about SEO differently: not just search engine optimization, but "search everywhere optimization." In this episode, Ryan and I talk about why long-form video can do much more than build a YouTube audience. It can give search engines and AI systems another surface for understanding who you are, what you know, and what your brand should be associated with. We also get into the growing importance of third-party trust signals, where traditional SEO still fits into AI search, and some of the GEO advice Ryan thinks marketers should be questioning. In this episode: Why Ryan thinks marketers should shift from "search engine optimization" to "search everywhere optimization" Why trust signals and third-party surfaces matter more as brands try to build visibility beyond traditional Google search Why Ryan has "never been more bullish" on YouTube as an AI search marketer How YouTube can become the foundation for blog posts, newsletters, short-form video, and other content Where to start if your brand wants to build a YouTube presence, from defining your ICP to finding the topics they're actually searching for Why Ryan recommends at least one long-form YouTube video a week — and why he favors evergreen content over constantly chasing trends The relationship between traditional SEO and AI search optimization, and why Ryan pushes back hard on claims that SEO is dead Where llms.txt fits into Ryan's strategy — and why he considers it a small piece of a much bigger visibility puzzle Why podcast appearances, media coverage, speaking, video, and other off-site signals can help establish what a person or brand is known for Why starting your own podcast or another form of long-form content can create a foundation for visibility across multiple platforms I'm an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI search measurement is getting more sophisticated, but is the data becoming more reliable? In this week's Found in AI news update, Cassie Clark covers Bing's new Topics Portfolio beta, Ahrefs research showing shifts in ChatGPT citations toward primary sources, and Nozzle's findings about misleading Google results served to rank trackers. She also explores why missing ChatGPT referral tracking data could make AI-driven traffic harder to measure, plus Yahoo's latest AI search experiment. In this episode: Bing Topics Portfolio: What the new AI Performance beta reveals about topic-level citations, grounding queries, and content opportunities. ChatGPT citation trends: Why primary sources may be gaining ground and what the Ahrefs findings mean for brands publishing original content. Google SERP tracking concerns: What Nozzle found in 27.5 million search results pages and why marketers should validate sudden ranking changes. ChatGPT referral attribution: Why missing UTM parameters and referral data could make AI search traffic appear to decline even when visits are still happening. Yahoo's AI search tests: How follow-up questions are becoming part of the search experience. -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI , Cassie Clark talks with content marketer Ben Hale about what actually changes when you start creating content for AI search — and what doesn't. Cassie and Ben talk about how audience behavior should determine which AI engines you prioritize, why distribution is becoming an increasingly important part of content strategy, and how content needs to change when it moves from your website to platforms like Reddit. They also dig into the difference between AI mentions and citations, whether getting cited is actually enough to call your strategy successful, and how marketers can test new AI search tactics without chasing every new optimization trick that comes along. In this episode: Why you shouldn't treat AI search engines as a monolith How to decide which AI engines actually matter to your audience Why third-party distribution belongs in your AI search strategy Why copying brand content directly onto Reddit doesn't work How to create product and comparison content that's actually useful How content structure can affect AI citations Why getting cited is only a leading indicator of success The difference between AI mentions and citations What still matters about writing for humans How to design AI search experiments with clear timelines and success criteria Why marketers need to be willing to abandon tactics the data says aren't working -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/ Wondering what AI search means for your business? Cassie Clark Marketing helps startups and enterprise brands understand how AI systems discover and recommend them, identify what affects their visibility, and develop executable strategies. Services include team training, AI visibility diagnosis, strategic consulting, and fractional marketing leadership. www.cassieclarkmarketing.com

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI search is moving beyond citations and recommendations. As consumers use AI to discover businesses (and personal agents begin browsing the web on their behalf), brands need to think about the entire information environment surrounding them. In this episode of Found in AI , Cassie Clark breaks down Google’s updated guidance on main content and fake authors, new data showing rapid growth in AI-powered local search, and Profound’s research into personal agents like Muse and Instinct. Together, these developments point to a larger shift: AI visibility is becoming less about optimizing for a single answer and more about whether humans and AI agents can discover, understand, verify, and act on information about your brand. In this episode: What Google’s new “good main content” guidance means for SEO and GEO Why content structure matters without becoming another GEO hack Why brands cannot manufacture authority with fake experts How AI is changing local business discovery Why AI recommendations still trigger additional verification How personal agents like Muse and Instinct browse the web What agent-driven discovery could mean for websites and marketers Why AI visibility and agent readiness are becoming connected problems -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Google is expanding AI Mode’s monitoring capabilities, letting users have Google continuously watch the web for new information instead of repeatedly running the same search. In this episode of Found in AI , Cassie Clark looks at what persistent search could mean for content freshness and AI search visibility. Cassie also breaks down new research from Graphite analyzing nearly 500,000 AI shopping responses across ChatGPT and Google. While large and small retailers appeared at similar rates among cited sources, major retailers were significantly more likely to become the actual recommendation — another example of why citation presence and recommendation presence should not be treated as the same AI visibility metric. Plus, Google Search Console adds reporting for multimodal searches originating from tools including Google Lens and Circle to Search, and new research from Perplexity explores why retrieval systems may need more than the single passage containing an answer to provide enough context for a useful response. In this episode: Why Google AI Mode monitoring changes the traditional search journey What persistent search means for content freshness What Graphite found after analyzing nearly 500,000 AI shopping responses Why being cited by an AI system does not guarantee your brand will be recommended How prompt language can affect which retailers AI recommends Google Search Console’s new multimodal search reporting Why search intent increasingly exists without a traditional typed query What Perplexity’s contextual embedding research tells us about AI retrieval Why structuring content for AI shouldn’t mean removing useful context -- Found in AI covers AI search visibility, generative engine optimization (GEO), answer engine optimization (AEO), AI search measurement, and the changes marketers need to understand as platforms like ChatGPT, Google, and Perplexity reshape search and discovery. Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email her at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI , Cassie Clark welcomes back Tommy Landry, founder of Return On Now and author of The Signal and the Source , for a conversation about the connection between AI governance and AI search visibility. Internally, companies are connecting AI to CRMs, reporting systems, content workflows, sales data, and other sources of business information. Externally, AI systems are interpreting websites, third-party platforms, brand messaging, reviews, documents, and other signals to understand what a company is and what it does. And when those signals are incomplete, outdated, inconsistent, or just plain wrong, AI can still produce a very confident answer. Cassie and Tommy discuss why companies need human checkpoints around AI-powered workflows, who should be responsible for those checkpoints, and why AI governance can't simply be handed to one department. They also explore what this means for GEO and AI search visibility, including why brands need to think beyond citations and start paying closer attention to how they're actually represented inside AI-generated answers. In this episode: How internal AI governance connects to external AI visibility What happens when AI is working with inaccurate or outdated company data Why inconsistent messaging across sales, marketing, and other departments can become an AI visibility problem Where humans need to remain in the loop Who should be responsible for reviewing AI-generated outputs Why AI governance requires subject matter expertise How automated content workflows can create brand and messaging problems Why AI search visibility is about more than tracking citations What it means to measure your brand's AI representation Why accurate positioning matters before a customer ever reaches your website How third-party signals can shape what AI systems understand about your company Why AI governance is becoming a cross-functional business problem Tommy also shares the thinking behind his new book, The Signal and the Source , and his framework for managing AI across both internal workflows and external visibility. Find it on Amazon. -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI is moving beyond answering questions and toward taking action on our behalf. But as agents handle more of the customer journey, what happens to the websites and publishers that make AI-powered discovery possible? In this episode of Found in AI , Cassie Clark breaks down two developments that reveal different sides of the future of search. First, Meta introduces Muse , a personal AI agent designed to complete tasks on a user’s behalf. Cassie explores what the shift from AI answers to AI actions could mean for brand discovery, the customer journey, and why being recommended by an AI engine may no longer be enough. Then, we turn to a story that deserves more attention: Yahoo Scout . Yahoo CEO Jim Lanzone is making the case for an AI search experience that keeps publisher links visible and preserves opportunities for referral traffic. Cassie examines why that approach matters, what it could mean for the economics of the open web, and why marketers need to look beyond citations when measuring AI visibility. In this episode: What Meta’s Muse reveals about the shift from AI search to AI agents Why brands need to think about agent readiness, not just AI visibility How Yahoo Scout approaches AI-generated answers and publisher links Why citations and referral traffic are not interchangeable What the future of AI discovery could mean for marketers, publishers, and the open web Stories covered: Meta: Introducing Muse, a Personal AI Agent The Next Web: Yahoo Scout, Jim Lanzone, and the Future of Publisher Links -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Does ChatGPT recommend the same brands to everyone? In this episode of Found in AI , Cassie Clark talks with Joao from Friction AI about new research examining how personalization changes the brands recommended by ChatGPT, Gemini, Claude, and Perplexity. The study compared responses collected through APIs, anonymous AI accounts, and accounts that had been primed with specific user personas over two weeks. The results show that personalization does influence brand recommendations — but the effect varies considerably depending on the AI platform. Cassie and Joao discuss: How ChatGPT, Gemini, Claude, and Perplexity respond differently to personalization What changed between API, anonymous, and personalized responses Why geography can affect the brands and sources AI systems surface What personalization means for local and global brands Why creating more content isn't automatically the answer when your brand isn't appearing What marketers should understand about the methodology behind AI visibility tools Why personalization doesn't make AI visibility measurement useless — it makes repeated measurement more important Read the research: The original research report: The Personalization Gap: How a Model's Knowledge of the User Reshapes Brand Recommendations in Generative AI Cassie's insights Friction AI's insights -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/ Wondering what AI search means for your business? Cassie Clark Marketing helps startups and enterprise brands understand how AI systems discover and recommend them, identify what affects their visibility, and develop executable strategies. Services include team training, AI visibility diagnosis, strategic consulting, and fractional marketing leadership. www.cassieclarkmarketing.com

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe OpenAI is testing a new kind of ChatGPT ad that doesn't just send users to a landing page. It starts a conversation. In this Found in AI news update, Cassie Clark breaks down OpenAI's new Sponsored Agents, Google's latest agentic commerce tools, and a new publisher licensing program that raises some interesting questions about how much Google can actually measure inside AI search. You'll learn: How OpenAI's Sponsored Agents could change the traditional ad-to-website journey Why ChatGPT ads point toward a much bigger shift in agent-mediated commerce How Google is bringing Business Agents and more AI shopping capabilities into the customer journey Why Google's new AI share-of-voice reporting for retailers is worth watching How Google's pay-per-value publisher program complicates the conversation around AI search measurement Why marketers need to think beyond AI visibility and start preparing for agent readiness -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI , Cassie Clark talks with Leah Nurik, CEO and co-founder of Brandi AI, about why brands need to think much more broadly about what influences their visibility in AI-generated answers. Cassie and Leah discuss why GEO is becoming a brand marketing and communications problem, not simply an extension of traditional SEO. They also dig into the role PR and earned media can play in establishing authority, why the sources that matter for AI visibility vary by industry, and why authentic storytelling may be more durable than trying to find shortcuts for influencing AI systems. They also talk about what makes a story compelling enough to earn media coverage, how brands can identify stories that actually add something new to their industry, and what may happen as AI-generated answers become a bigger part of the buyer journey. In this episode: Why Leah believes AI search represents a new buyer journey Why GEO extends beyond traditional SEO and your website How PR and earned media can influence AI visibility Why authority signals differ from one industry to another The role of peer reviews, user-generated content, and third-party coverage What makes a brand story interesting enough for journalists to cover Why uniqueness matters for both PR and AI search How brands can build visibility that may be more resilient to model changes Where AI search could be heading over the next five years -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this Found in AI news update, Cassie Clark breaks down Peec AI’s research into OpenAI’s Labrador retrieval index, including the separate indexes identified for web content, news, shopping, YouTube, PDFs, and more. Then, we look at Common Crawl’s analysis of more than 584,000 llms.txt files and what it tells us about the confusion surrounding llms.txt, robots.txt, and AI crawler access. Finally, Microsoft is preparing businesses for a future where AI agents don’t just help consumers discover products — they help choose and buy them. Microsoft’s latest agentic commerce guidance shows why structured, accurate, and current product data could become critical as AI moves from answering questions to taking action. In this episode: What Peec AI discovered about ChatGPT’s Labrador search index Why ranking in Bing isn’t a proxy for ChatGPT visibility How freshness appears within ChatGPT’s retrieval infrastructure OpenAI’s experiments with its own shopping index What Common Crawl learned from 584,107 llms.txt files The difference between llms.txt and robots.txt Why llms.txt does not control AI crawler access Microsoft’s recommendations for preparing for agentic commerce Why structured product data matters when AI agents are shopping The difference between AI visibility and agent readiness Why businesses should prepare for AI discovery even while the technology continues to change Sources Peec AI: “ChatGPT Built Its Own Search Index” Search Engine Journal: “Common Crawl Finds Widespread Confusion Around llms.txt & robots.txt” Microsoft Advertising: “How Businesses Win When AI Does the Shopping” -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Google is giving us a pretty clear look at what comes after AI search visibility: AI agents that don't just recommend brands, but help consumers take action. In this week's Found in AI news update, I'm looking at several recent Google developments that make much more sense when considered together. Google DeepMind says Gemini is evolving from a model into an agent. Meanwhile, Google is adding more of the customer journey directly into Search and AI Mode, including flight price tracking, hotel research and booking, product discovery, visualization, price comparison, and more. So, what happens when getting recommended by an AI engine is only step one? In this episode: Why Google DeepMind is thinking beyond the chatbot How AI Mode is expanding from travel research into hotel booking What Google's home decor features tell us about the changing buying journey Why AI search visibility is still critical, but may actually be the beginning of the journey The difference between being recommended by an AI engine and being ready for an AI agent to take action Why agentic commerce will require more than content and SEO teams alone Plus, I share why marketers should start asking a new question: Once an AI engine finds, understands, trusts, and recommends your brand, can an AI agent actually do something with it? Resources mentioned: Google DeepMind on Gemini's evolution from model to agent Google's new AI Mode travel and hotel booking capabilities Google's AI-powered Search features for home decor Programming note: Found in AI is taking a short Labor Day break, so there won't be a Tuesday episode next week. We'll be back with a new episode the following Thursday. I'm an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Daniel Horowitz has spent more than a decade in SEO and now works as an enterprise SEO strategist at Salesforce, where he continues to lead AI search work for Informatica. One of the projects his team is testing challenges a pretty fundamental piece of the traditional B2B content funnel: gated content. Instead of locking valuable research, customer stories, and insights entirely inside PDFs, they're experimenting with a hybrid approach that makes the main ideas accessible as HTML while preserving the full gated asset for lead capture. Because if your best information is inaccessible to AI engines, they'll still answer your buyer's question. They may just answer it using someone else's information. In this episode: Why Daniel still considers SEO foundational to AI search — and where he thinks the two start to diverge Why creating more content isn't necessarily the answer when valuable information is already buried inside your existing assets How Informatica is testing a hybrid gating strategy that makes the main ideas from PDFs accessible without completely abandoning lead capture What Daniel's team has seen so far from turning gated information into accessible, answer-first content Why strong point-of-view content can give AI engines something distinct to associate with your brand What "chunking" actually means — and why it doesn't mean chopping every article into tiny pieces Why Daniel is experimenting with moving key takeaways from the bottom of articles to the top How outdated website content can continue shaping what AI engines believe about your company, even when those pages aren't driving meaningful search traffic The old Informatica product page that was reinforcing an outdated brand perception — and what happened after Daniel's team rewrote it Why monitoring how AI engines characterize your brand can uncover a much bigger positioning or business problem What Daniel has learned about getting enterprise stakeholders and senior leadership on board with AI search initiatives I'm an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/ Wondering what AI search means for your business? Cassie Clark Marketing helps startups and enterprise brands understand how AI systems discover and recommend them, identify what affects their visibility, and develop executable strategies. Services include team training, AI visibility diagnosis, strategic consulting, and fractional marketing leadership. www.cassieclarkmarketing.com

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI search may have had a quieter news week, but several updates from Google and Yahoo point to a bigger shift in how people discover information online. Google is expanding personalization across Search and Discover, including new ways for users to choose the publishers they want to see more often. It's also bringing link carousels for developing topics into AI Mode, creating additional opportunities for publishers and brands to earn clicks from AI-generated answers. Meanwhile, Google's John Mueller says there's still “nothing really special” websites need to do for generative AI responses in Search. I explain why I largely agree with that advice when we're talking about Google, and why marketers shouldn't apply it to the entire AI search ecosystem. Plus, Yahoo is leaning into Yahoo Scout and its history as the original guide to the internet. Could AI give Yahoo another chance to become a meaningful discovery destination? In this episode: How Google's Preferred Sources feature changes the conversation around brand authority Why Google's new AI Mode link carousels matter for marketers and publishers What John Mueller's latest comments actually mean for GEO and AI search optimization Why Yahoo Scout is worth watching as AI search continues to fragment What marketers should learn from Yahoo's broader push for users and relevance A quick update on Google's August 2026 spam update Why brands need to become sources that both people and AI systems want to find Mentioned in this episode: Google: New ways to personalize Search, Discover and Google News Search Engine Roundtable: Google Says Nothing Special Needed for Generative AI Search Responses Search Engine Roundtable: Google AI Mode Gets Link Carousels for Developing Topics Yahoo Scout I'm an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Reddit's share of ChatGPT Search citations fell by 86% in just four days — and nobody, including the firm that tracked it, claims to know exactly why. In this episode, we break down what actually happened, why the drop looks completely different across ChatGPT versus Google's AI Overviews and AI Mode, and what the ongoing Reddit-Google tension might have to do with it. Then: a Google spam update rolled out with zero new policies, but a clarification from Google's John Mueller complicates the story trackers were already telling about it. We break down why blaming the wrong update for ranking volatility means fixing the wrong thing. Plus, a quick look at Google Trends' new Explore Maps feature and what it's actually useful for. In this episode: Why Reddit's ChatGPT citation share fell off a cliff, while its Google AI Overviews and AI Mode citations only slid gradually What the Reddit-Google licensing tension might (or might not) have to do with it Why volatility before an update announcement usually isn't that update What Google Trends' new regional Explore Maps add for content research I'm an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Let’s connect: LinkedIn → Cassie Clark | AI Search Visibility Consultant Website → https://cassieclarkmarketing.com Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe A few stories with real strategic implications, and one that's generating more heat than light this week. First: Microsoft Clarity adds branded vs. non-branded query segmentation to its AI Citations dashboard. Cassie breaks down what the new filtering actually shows you, why separating brand-led demand from category discovery changes how you interpret your citation data, and what Share of Authority looks like when you can finally split it by query type. Then: LinkedIn publishes its first comprehensive B2B AI search guide, backed by internal data and eighteen months of their own testing. Cassie pulls out what's actually useful, including why LinkedIn is the number one most-cited domain for professional queries in AI search, how articles and posts do different jobs in the citation ecosystem, and the org alignment point that most brands are still missing. Plus: Sundar Pichai announced Gemini hit one billion monthly users, Shopify's Q2 data shows AI-referred sessions growing 197% year-over-year with double the conversion rate in research-heavy categories, and the Claude watermarking story — what we actually know, what's still speculation, and why you shouldn't change your workflow yet. In this episode: What branded vs. non-branded grounding query segmentation actually tells you How to use Share of Authority data now that you can filter by query type Why LinkedIn articles and posts do different jobs in AI search The org alignment problem LinkedIn's own guide surfaces What Profound's citation timing data means for how you evaluate new content What Gemini's milestone signals about where AI search is headed What Shopify's Q2 data says about buyer behavior in research-heavy categories What we actually know about Claude's watermarks — and what's still noise I'm an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Let’s connect: LinkedIn → Cassie Clark | AI Search Visibility Consultant Website → https://cassieclarkmarketing.com Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy , on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/