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 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/

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/

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/

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/

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/

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/

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/

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

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

Send us Fan Mail It's the official one-year anniversary of Found in AI! In this solo episode, I go back through the entire Found in AI archive and pull out the five-step strategy for AI search visibility — built from a year of guest conversations, prompt tests, and a few things I got wrong along the way. Whether you've been listening since episode one or you just found the show, this is your starting point. What's covered: Why AI search visibility is a cross-functional problem that shows up looking like a content problem The five-step strategy: Describe → Structure → Refresh → Corroborate → Measure How the FSA Framework (Freshness, Structure, Authority) fits into a broader visibility strategy Why fixing your brand description across surfaces is step one — before you touch your content The weekly assignment you can do in an afternoon to find your actual roadmap Episodes mentioned: Step 1 — Description Is Your AI Visibility Problem Actually a Messaging Problem? — with David Kirkdoffer How Does Local SEO Translate to AI Search Visibility? — with Tommy Landry Step 2 — Structure (FSA) How Do AI Engines Decide What to Cite? The FSA Framework Explained Stop Optimizing Keywords for ChatGPT — with Shane Tepper What AI Engines Actually Want (And Why Your Blog Posts Aren't It) — with Bryan McAnulty Step 3 — Freshness (FSA) How Approval Layers Slow Down AI Search Visibility — with Rose Ann Mullet Why Aren't AI Engines Citing Your Content? (Hint: You're Missing Knowledge Graph Enrichment) — with Paul Rowe Step 4 — Authority (FSA) What Does It Take To Actually Get Cited in AI Search? — with Jonathan Bentz The 24-Hour Reddit Citation — with Carl Peterson SEO and PR Are Finally Married (And AI Search Is Why) — with Basha Coleman Step 5 — Measurement What Do Bing's AI Performance and ChatGPT Ads Mean for Search? What is an AI Visibility Audit? (And Do You Need One?) AI Competitive Intelligence: How to Track What's Citing Your Competitors — with Vlad Pivnev If you're new here: New to AI search: What's the Difference Between SEO, AEO, and GEO? How Do AI Engines Decide What to Cite? The FSA Framework Explained Should You Skip SEO and Go Straight to AI Search? [2026 UPDATE] Trying to measure it: What is an AI Visibility Audit? How Should Brands Measure Visibility in AI Search? What Do Bing's AI Performance and ChatGPT Ads Mean for Search? Selling this internally: Is Your AI Visibility Problem Actually a Messaging Problem? — with David Kirkdoffer How Approval Layers Slow Down AI Search Visibility — with Rose Ann Mullet You Can't SEO Your Way Into AI Search Visibility Want the arguments: SEO Agencies Have 2 Years Left — with Gilad Pichar "Good SEO is Good GEO." But Is That True? AJ Ghergich / Botify three-part series (Parts 1–3) 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

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Two stories in a slow week. First, Microsoft launched its first Advertising product newsletter and used it to announce that Microsoft Clarity's AI visibility suite now reports citations, citation share, grounding queries, and share of authority — a platform-defined, free metric for how often AI systems pick your domain over everyone else's. Cassie breaks down what's actually in the dashboard, why it matters that Microsoft framed this as bringing "the same rigor and transparency of reporting" to the AI era, and the org problem hiding in plain sight: this entity data landed in a paid media newsletter, with paid media recommendations attached. Then: Google told The Verge that Reddit gets no special preference in its ranking systems or AI search features — while Reddit absorbs a core update, a spam update, and a wave of people gaming it for AI placement. Cassie makes the case for why concentration risk on any single third-party surface is the real story there. Plus a note on why newsletter content is worth more than it used to be, and what Microsoft publishing this on LinkedIn might be doing. In this episode: What Microsoft Clarity's four AI visibility metrics actually measure Why "share of authority" being platform-defined matters The question to ask your team this week about Clarity How to treat Microsoft's conversion stats before you put them in a deck What Clarity shows you — and the layer it doesn't Why a newsletter with a public archive is a retrieval surface, not just a list The gap in Google's Reddit denial Third-party mention concentration and why it's a risk Resources: Microsoft's Product Newsletter August 4, 2026 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 7-Day 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

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Rose Ann Mullet spent years as a content lead inside a major corporation where every piece of content moved through four or five approval layers. She streamlined the process and is proud of the system they still use. It still took a considerable amount of time to get anything out the door — which turns out to be an AI visibility problem, not just a workflow one. Then she left, started RM Content and Consulting, and began applying the same framework to solo attorneys who can publish the same afternoon they decide to. Same signals, radically different speed. This conversation is about what that gap actually costs. In this episode: What it looks like to push for AI visibility from inside an org where leadership says yes in principle and nothing moves The "if we get the SEO right, AI will follow" argument, and why Rose and her SEO manager both knew better A 50% lift in ChatGPT-referred traffic after restructuring one section of a corporate site — and why they never got to properly test it Why regional and local offices describing the brand differently is an entity problem, not a brand-consistency nitpick Freshness as a retrieval signal, and why your approval chain sets a ceiling on it How Rose applied Freshness, Structure, and Authority to a solo attorney's personal brand, LinkedIn, and dormant blog Getting that attorney recommended by AI within 30 days — including the competitive-set caveat that makes the result honest Watching AI characterize a client using language from content Rose ghostwrote for him Why competitor analysis is now a weekly exercise instead of an annual one Where local PR fits into a visibility strategy for service businesses 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/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI Overviews now appear in roughly 43% of Google searches, up from 15% a year ago. But buried in the same dataset is a number almost nobody is quoting: as of May 2026, only about 6.8% of U.S. ChatGPT desktop queries returned an answer that cited anything at all. Citations are growing fast. They're also still the exception. This week's news update covers four developments that all point the same direction — your brand's visibility is increasingly being determined on surfaces your content team doesn't own and can't see. The Similarweb data behind the 43% figure, why the 6.8% citation rate is the more useful number, and what it means that ChatGPT's click-through share jumped from about 25% to nearly 60% after its May update Search Console platform properties going global — verifying TikTok, Instagram, X, and YouTube accounts as properties, plus what Google's new analysis guide reveals about the "what people are saying" carousel and the query groups card Why Google's consumer post about AI Mode is a strategy document in disguise, and what changes when Search starts calling stores and booking tickets instead of just answering questions The correction gap: why old news resurfacing inside AI summaries is an entity accuracy problem, and why suppression is the wrong fix 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 7-Day 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

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly 3-2-1 on AI search + marketing: subscribe Most brands treat AI search visibility as a technical problem. Add the schema, clean up the structure, fix the crawl paths, wait to get cited. Then nothing happens. David Kirkdorffer has been doing B2B marketing since the nineties and now works with CMOs, CROs, and CEOs on exactly this. His argument: the technical layer is a building block, not the answer. What actually gets pulled into an AI-generated answer is the language on your page — and if five different teams are describing your company five slightly different ways, you've given the model nothing to be confident about. In this conversation, David and I get into why messaging drift quietly moves your brand into a different category, why product marketing may be the highest-leverage seat in your AI visibility strategy, and why large enterprises are often better at this than scrappy startups (for reasons that have nothing to do with budget). What we cover Why SEO gets you on the shelf but doesn't get you quoted "Word math" — how small wording changes move your brand into a different semantic category without anyone noticing The hub-and-spoke model: product marketing as the source of messaging for PR, demand, partner, and sales Corroboration as a trust signal, and why consistency across surfaces beats volume Why big companies quietly solved this decades ago, and what small brands can borrow The digital footprint gap, and why challenger brands compete against a mountain of existing content How LLMs decompose a query, fan it out, and let retrieved chunks compete on completeness and semantic alignment Why efficiency is a retrieval criterion most people ignore The hiring problem: why "AI search optimization" job descriptions are mostly technical SEO What happens when your predecessor's positioning is still live across the internet 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 7-Day 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

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly 3-2-1 on AI search + marketing: subscribe This week was one of the busiest news cycles we've had in a while. Five stories, all connected. What we cover: Alphabet Q2 2026 earnings: Google reported $119.8 billion in revenue, up 24% year-over-year, with Google Cloud growing 82%. Search revenue hit $63.3 billion and queries are at an all-time high. But here's the tension: AI experiences are driving more search activity while simultaneously sending less traffic to publishers. The publisher revolt: Reddit, USA Today, Politico, Reuters, and The Economist are all reconsidering how much access they give Google. According to Semrush data, organic Google traffic to USA Today's US site fell nearly 50% between June 2025 and June 2026. Business Insider dropped more than 85%. Reddit's $60 million/year Google licensing deal is up for renewal — and Reddit is weighing whether it's still worth it. Google's VP of Search on where search is headed: Tech Brew published a sit-down with Liz Reid this week. She said links aren't going away, that AI Mode and Gemini have different north stars, and that personalization is the next frontier. The OpenAI/Hugging Face security incident: OpenAI's models found a zero-day vulnerability, escaped a testing sandbox, gained internet access, and compromised Hugging Face's production infrastructure — all while trying to solve an internal benchmark. OpenAI called it an unprecedented cyber incident. Claude's "Record a Skill" feature: Anthropic launched a new feature in Claude Cowork that lets you record a screen walkthrough of a task and turn it into a reusable skill. Available on Pro, Max, and Team plans. Resources mentioned: Alphabet Q2 2026 earnings Tech Brew interview with Liz Reid OpenAI + Hugging Face security incident disclosure Claude "Record a Skill" announcement 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 7-Day 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 Substack → https://substack.com/@cassieclarkmarketing YouTube → https://www.youtube.com/@foundinaipodcast

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly 3-2-1 on AI search + marketing: subscribe Vlad Pivnev has been doing digital marketing for 16 years. Two years ago, he watched AI start dismantling the traditional agency playbook in real time and decided to build toward it instead of around it. He's now CEO of Stive, where his team runs competitive intelligence, LLM visibility, and AI-driven marketing strategies across hundreds of clients. In this episode, we talk about what his agency has learned from running over 100 experiments, the five factors that determine whether a brand shows up in AI-generated answers, and why competitive intelligence — once a once-a-year project — is now something you can run weekly. We also get into something I think gets underused in AI visibility strategy: tracking which sources are citing your competitors , not just where your brand appears. In this episode: Why 90% of Vlad's experiments produce nothing (and why he runs them anyway) The five-factor framework his team uses to diagnose AI visibility Why LLMs prefer unlinked brand mentions over links to your website What brand clarity actually means when an LLM is reading about you How to use competitive citation data to find your next distribution move If you're listening to this and thinking I need someone to lead this for me, that's what I do. 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 7-Day 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

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly 3-2-1 on AI search + marketing: subscribe AI search personalization just got a lot more personal. This week Google added Calendar to AI Mode's personal context layer — and the content strategy implications go way deeper than "cool, I can schedule a meeting from search." Plus: new data on ads in AI Mode, and John Mueller says something that contradicts Google's own documentation. What we cover: Google Calendar joins AI Mode — AI Mode can now read your schedule alongside your Gmail and Photos, meaning two people typing the exact same query can get two completely different answers. What that means for how you think about content strategy and knowing your buyer's context. Ads now appear in 1 in 3 commercial AI Mode queries — SE Ranking analyzed 50,000 keywords and found CPC is the strongest predictor of ad presence. The big takeaway: buying an ad does not help you get cited as a source. 88% of advertisers weren't cited for the keyword they were advertising on. Paid and organic are two separate games. John Mueller softens on A/B testing — Google's documentation warns that long-running tests could be flagged as deceptive. Mueller said this week there's no actual penalty for varying content. What that means if you're running page tests to see what gets cited in AI engines. If you're listening to this and thinking I need someone to lead this for me, that's what I do. 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 7-Day 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

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly 3-2-1 on AI search + marketing: subscribe A question in r/AEO this week asked: "What is the most overrated AEO advice you've heard?" The answers were predictable — FAQs, llms.txt, separate pages for every question. None of it is actually bad advice. The problem is when those tactics are applied with an SEO mindset inside a strategy that was built for a different era of search. In this episode, Cassie breaks down why tactics alone keep falling short, and brings in the Semrush 2026 AI Visibility Index (126 million U.S. AI search prompts analyzed from January through April 2026) to back it up with data. What we cover: Why the "bad AEO advice" isn't actually bad, and what makes it fail Why AI search visibility is a whole-org problem, not a content team problem What a Strategic Source of Truth is and why AI engines need it The mentions vs. citations gap, and why a brand can show up in an AI answer without a single owned page being cited How category concentration shapes your AI visibility timeline What the "Universal 36" brands have in common and what it means for your strategy Why third-party coverage is now brand infrastructure, not a nice-to-have The 81% vs. 36% stat that should end the SEO vs. GEO debate What senior content strategists can do right now, even if they can't move the org yet If you're listening to this and thinking I need someone to lead this for me, that's what I do. 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 7-Day 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

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly 3-2-1 on AI search + marketing: subscribe This week's Found in AI covers three updates that, taken together, say the same thing: AI visibility is a cross-channel, cross-functional problem — and it's getting harder to ignore. In this episode: Google just launched platform properties in Search Console — a new property type that lets you track how your Instagram, TikTok, X, and YouTube content performs in Google Search and Discover. The SEO story is interesting. The GEO story is more interesting. OpenAI introduced GPT-Live, a full-duplex voice model that can listen and speak at the same time, with real-time web search running in the background. Voice search has been a talked-about trend for years. This is the version that might actually change behavior — and the implications for what AI cites in a spoken answer are worth thinking through now. And Search Engine Journal published a piece making the case that the people who drive GEO outcomes in most organizations are brand, PR, and editorial teams — not SEO. It's a take I've been making on this podcast for months. Worth breaking down what it actually means for how content teams get structured. If you're listening to this and thinking I need someone to lead this for me, that's what I do. 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 7-Day 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

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly 3-2-1 on AI search + marketing: subscribe If you've been publishing content and wondering why it's doing nothing for your AI search, this episode is for you. Bryan McAnulty, founder of Heights Platform and Latchloop, joins Cassie to break down something most brands are missing: the training data already has everything that existed before. Which means the only content worth creating right now is what's new, what's happening in real time, and what real people are actually saying. That reframe changes everything about how you approach content strategy in 2026. In this episode: Why most blog content is invisible to AI engines before you even publish it The difference between training data, live web search, and deep research, and why you need a strategy for all three How community content captures the conversational data LLMs can't get from training Why comparison and alternative pages are suddenly worth paying attention to again The trust gap: why 90% of general consumers still don't trust AI-generated answers, and what that means for brands If you're listening to this and thinking I need someone to lead this for me, that's what I do. 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 7-Day 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