Found in AI Ep 7: Why FAQ Schema is Your AI Search Secret Weapon

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

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

In this episode, I sit down with Romana Kuts, founder of SaaStorm, to talk about why structured data is the simplest — and most overlooked — fix for AI visibility.

You’ll learn:
• Why FAQ schema is one of the strongest signals for AI engines like ChatGPT, Perplexity, and Gemini
• How to write short, direct FAQs that actually get cited by LLMs
• Why author schema is essential for building trust and proving human authorship
• The difference between schema for SEO and schema for AI crawlers
• Whether llms.txt really matters — and what Romana’s client tests revealed

If you’ve been wondering how to adapt your SEO playbook for an AI-first world, this episode is for you.

Transcript: Why FAQ Schema is Your AI Search Secret Weapon

(Just FYI: This transcript has been cleaned for easy reading.)

Cassie Clark (00:00 – 00:59)
Every founder wants their content to show up in AI search, but most are missing the simplest fix: structured data.

Welcome back to Found in AI, the show about getting your business discovered in AI search. I’m your host, Cassie Clark — a fractional content strategist, founder of Cassie Clark Marketing, and currently CMO of ThoughtTree.

Each week, I sit down with my neighbors camped out in internet land to talk about what’s really working in AI visibility. In this episode, I’m joined by Romana Kuts, founder of SaaStorm, to unpack exactly how schema markup and those short, sweet FAQs can make your brand visible in AI engines.

Cassie (01:00 – 01:04)
Let’s start with the basics. Tell me who you are, what you do — all the things.

Romana Kuts (01:05 – 01:49)
Of course. My name is Romana, and I’m the founder of SaaStorm. SaaStorm is a B2B SaaS marketing agency, and we position ourselves as a revenue-focused agency because we like to be inside the client’s CRM — tracking MQLs, SQLs, pipeline.

We try to be as data-driven as possible. Our main strategies and services are content and SEO. Depending on the client, we also provide design, web development, and some PPC support. But mostly it’s about content, LLM optimization, and SEO optimization.

Cassie (01:49 – 01:54)
What have your clients been asking about AI search?

Romana (01:55 – 02:22)
That’s a good question. The first thing is always: How can we see if ChatGPT is citing us? Are we visible in AI?

The second question is: How do we get more traffic from ChatGPT? How do we become even more visible? Those are the two most common themes.

Cassie (02:22 – 02:26)
And are your clients already seeing results from changing their strategy?

Romana (02:27 – 02:58)
Yes, I would say so. First, you can always see referral traffic from ChatGPT — that’s easy to track. Second, we set up LLM tracking infrastructure for our clients. We can see what prompts are being used, how they show up in different models, and how we can improve visibility.

In Q3, we focused heavily on LLM visibility across the board.

Cassie (02:59 – 03:03)
And that’s not just for one or two clients — it’s everyone?

Romana (03:04 – 03:33)
Honestly, everyone. Out of nowhere, all of our clients started asking. My co-founder and I realized we had to adjust, so we proactively implemented LLM optimization and tracking across all clients. No extra charge — we just saw it as essential.

Cassie (03:34 – 03:51)
Before we dive into structured data, I have to ask: SEO is dead, SEO is alive, GEO is silly — what’s your take?

Romana (03:51 – 04:55)
I see those conversations on LinkedIn all the time. SEO isn’t dead. Nothing is dead — even cold calling isn’t dead.

What’s really happening is that LLM optimization, GEO, AEO — they’re all just variations of SEO. It’s still about doing the fundamentals well. The only shift is adding structured data and schema markup so your SEO content is also optimized for AI. If you’ve been doing good SEO, you’ll also perform well in LLM search.

Cassie (04:55 – 04:57)
I’ve been calling it “the alphabet.”

Romana (04:58 – 05:15)
Exactly. Every day there’s a new acronym: AEO (Answer Engine Optimization), GEO (Generative Engine Optimization), LMO (Learning Models Optimization). It’s endless. At some point, we just need to pick one.

Cassie (05:16 – 05:30)
For listeners who may be new to this, how would you explain structured data in plain English?

Romana (05:31 – 06:30)
When humans read a page, we see text, headings, images. But Google sees it differently — through code and schema.

Schema markup is like a set of signals. For example: This is an internal link. This is an FAQ. This is an author. Humans don’t see it, but crawlers do. It’s like letters in an alphabet for search engines.

Cassie (06:30 – 06:35)
What’s the difference between schema for SEO and schema for AI engines?

Romana (06:37 – 08:14)
There isn’t a huge difference, but AI crawlers read content differently. Google’s search engine was keyword-first. AI crawlers look at conversations and signals that say, This page is ready to be indexed by an AI agent.

That’s why I recommend FAQ schema. It mirrors how people ask questions in ChatGPT, Perplexity, or Gemini. When someone asks a long question, you want the AI to pull your direct answer. FAQ schema flags that.

Cassie (08:15 – 08:43)
What’s the best length for an FAQ answer? Short, long, somewhere in between?

Romana (08:44 – 09:50)
Short and direct. I ask my writers to keep answers under three sentences — 150–200 characters. No intros, no filler. If someone asks, What is knowledge management? the answer should start with Knowledge management is…

Also, don’t overdo it. Three to five FAQs per post is plenty. Any more and your blog starts looking like a FAQ dump instead of an article.

Cassie (09:51 – 10:09)
I’ve found three to five works well too.

Romana (10:10 – 10:50)
Exactly. We’ve seen GPT cite short FAQs almost word-for-word. The simple, clear answers get picked up the most.

Cassie (10:50 – 11:01)
Other than FAQs, what schema do you recommend adding?

Romana (11:02 – 12:14)
Author schema. With AI making it so easy to generate content, it’s important to show there’s a real human behind the article. Adding an author photo, name, LinkedIn profile, and short bio sends a strong signal of expertise.

Many companies still list “Company Blog” as the author. That’s a missed opportunity. EEAT (Experience, Expertise, Authoritativeness, Trustworthiness) matters — and schema helps prove it.

Cassie (12:15 – 12:39)
Do you add that manually or through automation?

Romana (12:40 – 13:04)
We implement it across the CMS at the code level, so it automatically applies to every article. Some clients add it manually, but system-wide automation is more efficient.

Cassie (13:04 – 13:25)
Looking ahead — will structured data matter less as LLMs get smarter, or more?

Romana (13:26 – 14:16)
I think it will matter more. Big companies are hiring AI content engineers, and engineering means coding. Schema, markup, and structured signals will only grow in importance. Even if LLMs improve, schema remains a reliable way to guide them.

Cassie (15:00 – 15:18)
There’s a lot of debate on LinkedIn about llms.txt. Should companies add it?

Romana (15:19 – 16:01)
We tested it with some clients and didn’t see much difference in traffic or citations. It may vary by industry, but in our experience, FAQ and author schema had a bigger impact.

Cassie (16:43 – 16:59)
Last question: If you’re advising a resource-strapped startup, what’s the 80/20 of schema?

Romana (16:59 – 17:57)
Start with FAQ schema and author schema. They’re simple, effective, and easy to implement. Even content writers can add them, or you can retrofit existing posts. Those two give you the most impact with the least effort.

Cassie (17:58 – 19:41)
That’s it for today’s episode of Found in AI. Big thanks to Romana Kuts of SaaStorm for breaking down how structured data drives AI visibility.

Here’s your experiment: pick one of your blog posts, write three short FAQs, and paste them into ChatGPT. Ask it to generate FAQ schema in HTML, then add the code to your CMS. Your readers won’t see it, but AI crawlers will. Watch your analytics over the next few weeks to see if those posts pick up AI-driven traffic or citations.

Quick ThoughtTree update: we’re launching beta for ThoughtLab and ThoughtSpace — our AI workspaces that work the way you think. If you’d like to test them out, we’d love your feedback. Visit www.thoughttree.io to sign up.

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