Breaking Your “Google Brain”: What AI Search Means for Marketers Today

Insights from Episode 80 of The GTM Kickback! featuring Lacey Miller 

We’re living through a massive shift in how people search, how content is surfaced, and what visibility really means in a digital world dominated by AI. But here’s the catch: most marketers are still stuck using playbooks built for Google.

On this episode of The GTM Kickback!, I sat down with Lacey Miller—Head of Marketing at Perigon—to unpack what comes next. Perigon isn’t your typical search engine. It’s what Lacey calls a context engine, designed to deliver not just links, but full, nuanced answers. And that makes her perspective on the future of content especially valuable. 

Our conversation touched on the rise of AI Visibility Optimization (AIVO), the shift in user behavior that’s driving it, and how marketers can start building content that not only reaches people—but also teaches the algorithms to see them as a relevant, trustworthy source.

A New Kind of Search Behavior 

One of the most interesting shifts we explored is how user behavior has changed with the rise of LLMs like ChatGPT, Claude, and Perplexity. Traditional Google searches are short and vague—three or four words, max. But AI tools are inviting people to think more like humans again. Users are typing in 14- to 17-word prompts. Full questions. Detailed scenarios. Real context. 

As Lacey put it, “People feel comfortable giving these tools more because they trust them to give more back.” That’s something no one ever said about a blue link list from Google. 

The product itself has become more conversational, so users naturally become more conversational too. That shift in tone—from list-seeking to insight-seeking—is one of the most important undercurrents in today’s content strategy landscape.

The Rise of AIVO 

Lacey and I discussed the awkward in-between stage we’re in right now. Everyone knows AI search is changing the game, but no one knows quite what to call it. GEO? LLM optimization? AI SEO? AIVO? Whatever term ends up sticking, the core idea is this: 

You need to structure your brand presence in a way that makes it legible to AI models. 

In the same way SEOs used to optimize for Google’s crawlers, today’s marketers need to optimize for how AI systems learn, absorb, and surface information. But this time, the inputs are completely different. 

LLMs don’t respond to keyword stuffing or backlinks. They respond to signals like: 

• How many credible sources mention your idea or brand 

• Whether the content is in a human, conversational format 

• If the insight you're offering is actually new or just derivative 

This is where AIVO really diverges from traditional SEO. It’s not about gaming a ranking algorithm. It’s about earning a seat in the conversation.

AIVO in Practice: Perigon's Approach 

At Perigon, Lacey has completely restructured their content strategy to reflect this reality. They don’t start with blog posts—they end with them. 

Their typical content flow now looks like this: 

• Start with a podcast, where real conversations happen and original thinking gets voiced. 

• Publish the full transcript, making the entire conversation searchable and indexable by AI models. 

• Highlight key Q&As or snippets from the conversation. 

• Only then write a blog post to summarize and reflect. 

• The blog is no longer the centerpiece—it’s the supporting act. 

This strategy is rooted in one fundamental belief: AI engines are learning by listening. And if your voice isn’t part of the broader conversation—through audio, text, public distribution—it’s not going to show up when someone asks a question your product should be answering. 

Experimentation Is the New Essential Skill 

There was one idea Lacey shared that should resonate with every founder, GTM leader, or marketer right now: if your team isn’t experimentation-first, you’re in trouble. 

There’s no set formula for AIVO. The models are constantly changing. Their black-box algorithms remain largely unknown. And the behaviors of ChatGPT, Claude, Gemini, and others differ in subtle but important ways. 

At Perigon, they’ve actually built internal tools to test the same query across multiple LLMs just to see what surfaces. Not only does this help them reverse-engineer visibility, it gives them early insight into gaps—places where their brand or product should show up but doesn’t yet. 

This kind of real-time feedback loop is going to become table stakes. You can’t afford to build your entire go-to-market motion around a channel you can’t see or understand. You have to test, track, and adapt constantly. 

Authentic Content Wins 

If there’s one thread that tied our conversation together, it’s this: authenticity is no longer just good branding—it’s good visibility. 

AI models don’t reward content that’s been said a thousand times before. They reward originality. Thoughtfulness. Human tone. Unexpected context. 

That means marketers who’ve been hiding behind templates, recycling blog formats, and treating AI as a content factory are going to lose. The AI doesn’t want to read more AI-written fluff. It wants unique voices, smart perspectives, and nuanced takes. 

And that’s actually encouraging. Because it means the most “visible” companies in this new era will be the ones who say something real. 

Final Takeaway: Back to Human 

Ironically, AI is pushing us to be more human. We’ve spent years optimizing for algorithms—writing for machines. Now the machines are telling us: if you want to be seen, you need to write like a person again. 

Lacey said it best: “Don’t be afraid to make your content more detailed, more conversational, and more real. If you had to explain your product to your grandmother, how would you do it? That’s what people—and AI—are craving right now.” 

The marketers who lean into that mindset? They’re not just going to survive this shift—they’re going to define it.