Found in AI Ep 4: How to Make Your Content Show Up in AI Search (with SEOforge’s Alex)

Writing for Humans vs. LLMs: What Actually Needs to Change? – 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: subscribeIn 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 monolithHow to decide which AI engines actually matter to your audienceWhy third-party distribution belongs in your AI search strategyWhy copying brand content directly onto Reddit doesn't workHow to create product and comparison content that's actually usefulHow content structure can affect AI citationsWhy getting cited is only a leading indicator of successThe difference between AI mentions and citationsWhat still matters about writing for humansHow to design AI search experiments with clear timelines and success criteriaWhy 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

1. Writing for Humans vs. LLMs: What Actually Needs to Change? 28:25
2. Google Updates Content Guidance as AI Agents Reshape Search 17:43
3. Are AI Visibility Tools Measuring the Wrong Things? 17:12
4. Google AI Mode Monitoring + Why AI Citations Don’t Equal Recommendations 12:59
5. Who’s Responsible for What AI Says About Your Brand? 20:39

Welcome to Found in AI, the podcast about getting your business found in AI search.

In this episode, I sit down with Alex, co-founder of SEOforge, to dig into what actually works when it comes to driving traffic from ChatGPT and other AI search engines.

You’ll learn:
• How to track and attribute high-intent traffic from ChatGPT
• Why unique insights get cited more often than keyword-heavy content
• The surprising differences between what ranks in Google vs. ChatGPT
• How to structure Help Centers (one question per article) so AI engines surface your brand
• Why hosting FAQs on your main domain matters for conversion

Transcript: How to Make Your Content Show Up in AI Search

Cassie Clark:
Every content marketer is asking the same question right now: what actually works in AI search?

If we haven’t met yet, I’m Cassie Clark. I’m a content strategist who helps startups and B2B brands get seen. And now that AI engines are part of how people search, that means creating content that shows up in AI-generated answers.

In today’s episode of Found in AI, I’m joined by Alex Secara, co-founder of SEOforge. He’s been deep in the trenches testing how ChatGPT, Perplexity, and other LLMs surface content — and what startups can do to actually earn high-intent traffic.

We dig into what’s different about AI search, why unique insight matters more than keywords, and how to structure Help Centers so LLMs pick up and cite your brand. Here’s part of our conversation.

Cassie:
I’ve seen a lot of people talking about the traffic that comes from AI search engines — those visitors are often high-intent customers, the ones who will actually convert. Did you just flat-out ask them how they found your brand? How did you know they came from ChatGPT and not Google or somewhere else?

Alex:
We did two things. First, we saw it in Google Analytics and Vercel Analytics — people were coming directly from ChatGPT. We had tracking set up, so we could see if someone came from that source, would they sign up, would they convert? We could directly identify those users.

Second, we added a question in onboarding: “How did you hear about us?” and made “ChatGPT” one of the options. At first we thought about saying “LLM” or “AI search,” but all the traffic was coming from ChatGPT, so we just listed it specifically.

Cassie:
That makes sense. ChatGPT is the one I use the most. Are you also seeing traffic from Perplexity and the others?

Alex:
Perplexity is second, but it’s still far behind ChatGPT in terms of volume. I’ve also seen some traffic from Gemini, and from Claude — but Claude traffic tends to show up only for deep-tech startups. I haven’t seen it drive much for industries like healthcare.

Cassie:
So it’s very industry-specific.

Alex:
Exactly.

Cassie:
Tell me about how SEOforge works. I know Google Analytics, but this is different because it’s about AI search, not just Google.

Alex:
Right. We took what we’d learned over seven months of experimenting — what strategies work, what kind of content performs, how it’s different from SEO — and built that into a platform.

We’d previously built tools where people could interact with multiple LLMs at once — ChatGPT, Gemini, etc. — so we understood how people use them to get answers. We could see if users clicked citations or just copied a company name and pasted it into Google.

At SEOforge, we create a set of prompts for you. We scrape Reddit to find user-generated prompts, we pull actual questions from LLM conversations, and we layer in keywords from tools like Ahrefs. We track those weekly — not through APIs, but by looking at results the way a user would see them.

Then we analyze the responses: where competitors show up and you don’t, where they’re cited and you’re not. Once you’re publishing content, we create prompt sets around that content to see what’s actually driving traffic, and we help adjust it based on LLM responses and best practices.

We also just wrapped up a study of 500,000 user queries across ChatGPT and Google. The findings let us give users concrete instructions: here’s what you need to do if you want more traffic from ChatGPT.

Cassie:
So what’s the big difference between what works on Google and what works on ChatGPT or other LLMs?

Alex:
They’re very different. Google is “10 blue links.” ChatGPT gives you a long answer — sometimes with 16 citations, sometimes only five. Most users get what they need right in the ChatGPT response, so they don’t go further.

What works best in ChatGPT — but not always in Google — is unique insight. On Google, broad keywords can carry you if you’ve optimized long enough. In ChatGPT, as the conversation goes deeper, the questions get more specific. That’s high-intent. If your content has the specific insight they need — and OpenAI’s crawlers have indexed it — ChatGPT is much more likely to cite you.

We always push people to create unique content and perspectives. No AI slop, no generic summaries. Alongside that, technical SEO still matters: schema, proper headings, FAQs. Large FAQ sections and Help Centers work especially well.

Cassie:
I read a post recently where someone renamed their blog “Knowledge Hub” but it was still just a blog. Would you recommend having a whole separate entity — like a Help Center — with deeper, question-based content?

Alex:
Yes. A Help Center should be structured differently. Every article title is a single question, and each page is just a long-form answer to that one question. No H2s, no multiple topics — just one Q&A per page.

This lets you go deep into product capabilities or user pain points you wouldn’t cover in a blog. It’s a great way to quickly generate content that AI engines can understand and cite.

Cassie:
That’s a neat idea. I’m thinking about how I could set that up on my own site. Are your clients already seeing results from this?

Alex:
Yes — it’s working really well. One thing to watch out for: a lot of platforms make you host Help Centers on subdomains (like help.domain.com). Those can get traffic, but it’s harder to convert that traffic into signups or actions.

We recommend hosting Help Centers on your main domain, just like your blog. It keeps authority consolidated and improves conversion.

Cassie:
That conversation gave me a lot to think about — especially how Help Centers can pull in high-intent traffic if they’re structured the right way. Over the next few weeks, I’ll be adding Help Desk–style articles to my own website and testing how they perform in AI search.

I’m Cassie Clark, a fractional content strategist who builds AI search–ready content systems for startups and B2B companies. If you want to talk about how we can make your content work harder in this new search landscape, connect with me on LinkedIn or visit cassieclarkmarketing.com.

Next week, I’ll share what I know about how AI search picks which answers to surface. Stay tuned.

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