Found in AI is a podcast for marketers, founders, and content strategists who want to understand—and win—AI search visibility in the new era of search.
Hosted by Cassie Clark, an AI search consultant and marketing strategist who works with startups and enterprise brands, the show explores how platforms like ChatGPT, Perplexity, Gemini, and Google's AI-powered search experiences find information, interpret brands, and influence buying decisions.
Each episode breaks down real-world experiments, SEO, GEO / AEO, and content marketing strategies designed to help brands get found in AI-generated answers, not just traditional search results.
You’ll learn how to:
-Optimize content for AI-driven search and answer engines
-Blend traditional SEO with AI search optimization
-Build entity authority across search, social, and AI platforms
-Drive traffic, leads, and trust as search behavior continues to evolve
If you’re trying to future-proof your content strategy and understand how AI is reshaping discovery, Found in AI gives you the frameworks, insights, and tactics to stay visible—wherever search happens next.
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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.
📬 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 .
HubSpot's Loop Marketing: Rethinking Marketing for the AI Era
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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 .
Are AI Visibility Tools Measuring the Wrong Things?
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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
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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.
📬 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
Bing's New AI Visibility Data, ChatGPT Citation Shifts & the Attribution Problem
📬 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.
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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.
Writing for Humans vs. LLMs: What Actually Needs to Change?
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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
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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.
Google Updates Content Guidance as AI Agents Reshape Search
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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
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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.
📬 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
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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.
Who’s Responsible for What AI Says About Your Brand?
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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
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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.
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.
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.
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.
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.
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.
Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A.
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.
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.
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.
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.
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.
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.
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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.
