Ep. 11 Found in AI: The Role of the Content Engineer

Google Is Moving From AI Search to AI Agents – 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: subscribeGoogle 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 chatbotHow AI Mode is expanding from travel research into hotel bookingWhat Google's home decor features tell us about the changing buying journeyWhy AI search visibility is still critical, but may actually be the beginning of the journeyThe difference between being recommended by an AI engine and being ready for an AI agent to take actionWhy agentic commerce will require more than content and SEO teams alonePlus, 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 agentGoogle's new AI Mode travel and hotel booking capabilitiesGoogle's AI-powered Search features for home decorProgramming 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/

1. Google Is Moving From AI Search to AI Agents 10:56
2. Is Your Best Content Invisible to AI Search? 27:41
3. Google AI Mode Gets More Links + Yahoo Scout’s AI Search Push 12:34
4. Does YouTube Help You Show Up in AI Search? 18:49
5. Reddit's ChatGPT Citations Just Dropped 86% + What It Means for AI Search Visibility 09:03

In today’s episode of Found in AI, I sit down with Josh Spilker, Head of Content and SEO at AirOps, to unpack how the rise of the content engineer is changing the way marketing teams build and scale content for AI search.

We cover:

• What the content engineer role actually is — and why it’s becoming essential inside modern content teams
• How AI workflows are transforming SEO, linking, and large-scale content operations
• Why content freshness and structured updates matter more than ever in AI-driven discovery
• The skills, systems, and no-code tools that define the next generation of content professionals
• How to future-proof your strategy by treating content like a product, not just a calendar

If you’ve been wondering what it takes to build content systems that scale — and how to stay visible as AI reshapes search — this episode is for you.

Transcript: The Rise of the Content Engineer

Cassie Clark: Everyone’s talking about AI replacing writers. Listen, I’ve heard those conversations. I’ve been part of them. And for a hot minute, I was worried, too. But the smarter conversation is about the new roles AI is creating.

Welcome back to Found in AI, the show about getting your brand found in AI search. I’m your host, Cassie Clark — content strategist and CMO. Today, we’re taking a slightly different turn. I’m sharing a conversation with Josh Spilker, Head of Content and SEO at AirOps. We unpack one of the most overlooked roles emerging in content right now: the content engineer.

If you’ve been wondering what it really looks like to build content for AI-first discovery, how to future-proof your workflows, and where the content engineer fits within a content team — this episode is for you.

Josh Spilker: My name’s Josh Spilker. I live in New York City and I’ve been here for about two years. I work at AirOps as the Content and SEO Lead, and I’ve been here around ten or eleven months. AirOps is a content operations tool that helps you build workflows for your content and see how you’re appearing in LLMs. We offer a visibility dashboard and workflows that help you take action on those insights.

Cassie: Before you joined AirOps, what was your pulse on AI visibility? Was that new territory, or were you already digging in?

Josh: AirOps started as a workflow builder, specifically around automating workflows using LLMs. I’d already been using AI to help create content, briefs, and drafts. I remember experimenting with OpenAI Playground two or three years ago, and other tools like Claude and Gemma. I used AI mainly to stress test ideas — asking ChatGPT things like, “You’re an expert at X, Y, and Z, what would you add to this?”

So when I started at AirOps, it felt like a natural fit. It aligned with where I saw content and SEO heading.

Cassie: You were looking into the crystal ball and saw AI coming.

Josh: Yeah. A big influence for me was Luke Thomas — I worked with him at Friday, and he later joined Zapier. He encouraged us to explore the possibilities of AI: play around with it, see what kind of drafts and outputs it could generate. That’s how I got into OpenAI Playground, probably around 2021 or 2022.

Cassie: And now it’s 2025, and it feels like things are shifting again with agents.

Josh: Definitely. The new ChatGPT agents are a good example — tools that can perform specific tasks for you. People in our office are buzzing about them.

Cassie: Same here. It’s everywhere on X. But I really wanted to talk to you about content engineers — because you’re one of the only people I’ve seen labeling it that way. In one of your LinkedIn posts, you said traditional content orgs were built for SEO and blog calendars, not AI synthesis. What does that shift look like in practice?

Josh: There are two things happening at once. First, AI workflows are helping automate the manual processes that content and SEO teams have always struggled with. Take internal linking, for example. In my old roles, I used to manage massive spreadsheets of URLs, mapping where each link should go. It’s tedious, but critical.

With AI workflows in AirOps, you can identify where content should connect based on topics or keywords, find the right anchor text, and automatically insert links in your CMS. You can do this accurately and at scale — as long as you double-check with a product-minded QA process. You start small, test, then expand.

Second, there’s content freshness. Depending on your industry, you need to update content regularly to stay visible in LLMs like ChatGPT and Perplexity. AI can surface regulatory or industry changes, then flag what needs updating. Keeping content fresh not only improves traditional SEO performance but also ensures visibility in AI-driven results.

Cassie: I love that. And quick break — if you’re enjoying this episode, make sure you hit subscribe so you don’t miss the next one. If you want insights like this straight in your inbox each week, sign up for my newsletter. The link’s in the show notes. Okay, back to it.

Josh, you mentioned content freshness. How often should teams be updating their content?

Josh: It depends on your industry. Fast-moving industries like SaaS, finance, and news usually need to refresh content every three to six months. Slower-changing industries — like real estate, ecommerce, or healthcare — can stretch that to six to nine months.

The key is to understand your freshness window. AI models are trained on different data sets, and users increasingly hit the “web search” button in ChatGPT or use tools like Perplexity, which are always pulling live data. So regular updates are essential to stay visible in both LLMs and AI-powered search features like Google’s AI Overviews.

Cassie: Makes sense. I wonder if those same freshness windows are built into AI models themselves.

Josh: It’s possible, but not confirmed. What we do know is that those patterns influence visibility — so staying current helps you maintain position in both traditional and AI-driven search.

Cassie: Let’s talk about AI search and the buyer journey — especially when clicks are disappearing. How should a content engineer think about influence when users get single answers from AI?

Josh: Great question. AI search is far more conversational. Queries are longer, more specific. Instead of typing “best project management software,” people are asking, “I run a 20-person SaaS marketing team — what’s the best project management software with Gantt charts and dependency tracking?”

That means more long-tail opportunities, but also more maintenance. Your content needs to stay updated to match those evolving, hyper-specific searches. What we’re seeing is less traffic overall — but higher intent and higher conversions from the traffic that does reach your site. For instance, Webflow has reported around 8–10% of new signups now come directly from AI chatbots. That’s significant.

Cassie: Wow, that’s a huge shift. So let’s define it clearly — what exactly is a content engineer?

Josh: I define a content engineer as a hybrid of strategist, technologist, and editor who builds systems for quality and impact. They think in words, but also in workflows. They design repeatable systems that measure visibility and velocity. Sometimes they even create their own no-code or low-code tools using platforms like AirOps or custom GPTs.

Cassie: What kind of skills or tech stack does that person need? Are we talking Python scripts, APIs, prompt engineering?

Josh: It depends on the organization. Some content engineers are technical and can use Python or JSON; others rely on low-code tools. What matters is systems thinking — being able to design scalable processes, not just write content. We’re seeing writers become content engineers, and technical folks moving into content. It’s a convergence.

Cassie: How does that differ from traditional content ops?

Josh: It’s about mindset. Traditional content ops often focus on execution and efficiency. Content engineering treats content like a product. It’s about building templates, processes, and even product requirement docs for content creation. It’s system-wide thinking — managing not just assets, but the entire infrastructure of a content program. Some people call it being a “context librarian” — maintaining a library of brand, product, and research knowledge that powers your workflows.

Cassie: That’s such a good description. A lot of our listeners are writers or marketing managers trying to figure out how to stay ahead of AI changes. What skills do they need to build?

Josh: It’s a mix. You still need subject matter expertise and a clear point of view — that’s what makes content stand out. But you also need to learn structured data, retrieval layers, and AI-assisted research and summarization. Automate parts of your process — briefs, outlines, updates — but keep your human quality standards. AI can help you expand your output and free up time for more strategic work.

Cassie: So if you were building a small team, would you hire a dedicated content engineer or train someone internally?

Josh: It depends on resources. At AirOps, we have a dedicated content engineer, but I also know how to build some workflows myself. You could start with a contractor or upskill your current team. What matters is having someone who understands this layer. It’s not going away — and every team will eventually need to account for it.

Cassie: I know you mentioned AirOps University in a recent post. If someone wants to learn these skills, is that a good place to start?

Josh: Definitely. AirOps University is free and hosted on Circle. We’ve turned our live cohort trainings into a self-paced course that walks through mapping and automating your content workflows. You can start experimenting right away with a free AirOps account.

Cassie: Perfect. If there’s one takeaway from this episode, it’s this: AI isn’t replacing content teams — it’s rewarding the ones who learn how to build systems that scale.

If you’re a writer or content manager looking to upskill, start small. Pick one part of your workflow — briefs, outlines, updates — and build a repeatable AI process around it. You’ll start thinking less like a writer and more like a content engineer.

I’m Cassie Clark, and this is Found in AI. If you want help future-proofing your content strategy, you know where to find me — on LinkedIn or at cassieclarkmarketing.com.

Remember: the future of content isn’t about who can write the most. It’s about who can build the smartest systems to make every word work harder.

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