Traditional SEO was straightforward in principle: be the best answer on a single page. “Who’s the best agent in Broadbeach Waters?” One page. One winner.

In Episode 6 of The AI Edit, Samantha McLean argues that model is no longer how search works — and breaks down what has replaced it.

AI overviews now sit at the top of Google search results. Rather than selecting a single best answer, they pull from multiple trusted sources to synthesise a response. Google reviews. Published articles. Website content. Social profiles. Different pieces of information from different places, assembled into a single answer.

“You’re no longer trying to be the best answer on a page,” Sam says. “You’re trying to be a trusted source that the AI will reference to build an answer. And that is quite a big shift.”

Also, AI overviews don’t just pull from any content – they heavily weight mentions across multiple independent domains. One website is not enough. Agents need a footprint: reviews, published articles, social profiles, and content with their name attached across different places on the internet.

Search behaviour is changing in parallel. Users are increasingly turning to ChatGPT and similar tools to ask complex, specific questions – not “bridging finance” but “I need to sell my current house to buy a new one, but I’m worried about timing. What’s the best way to handle financing and logistics so I don’t get stuck paying two mortgages?”

That kind of query demands a different kind of content to answer it.

The framework underpinning this, as Sam explains, is Google’s E-E-A-T: Experience, Expertise, Authoritativeness, and Trustworthiness. Google is looking for lived experience – which is why platforms like Reddit increasingly appear in AI-generated answers. It is looking for recognised authority — which is why brand reputation and website longevity matter. And it is looking for trust signals from multiple places across the internet: Google reviews, Facebook reviews, and published content with an agent’s name attached to it.

Sam draws an explicit connection to Ailsa, Elite Agent’s AI journalist, introduced in Episode 5. A published story on eliteagent.com about an agent’s sale – detailing their strategy, their expertise, and their process – is precisely the kind of E-E-A-T signal that AI overviews draw from. It is content on an independent domain with the agent’s name attached. It is, as McLean frames it, the digital letterbox drop from Episode 5, doing double duty – social proof for the neighbourhood and a trust signal for the AI.

The episode’s central line: “They can only find you if there’s content out there about you.”

Key takeaways:

  • Traditional SEO was about being the best answer on a single page. AI overviews pull from multiple trusted sources to synthesise an answer — the rules have changed.
  • Search queries are becoming more granular and conversational, particularly through AI tools like ChatGPT. Content needs to match that intent.
  • Google’s E-E-A-T framework — Experience, Expertise, Authoritativeness, Trustworthiness — determines which sources AI references. Reviews, published content, and trust signals all contribute.
  • Published stories about your work on recognised industry sites are E-E-A-T signals that AI can reference when building answers.
  • The bottom line: they can only find you if there’s content out there about you.

The AI Edit is a weekly series of short clips from the AI First Agent Accelerator. New episodes weekly.

Want the full system? Visit aiagentcourse.com.
Try Ailsa – AI-published stories that build your E-E-A-T: getailsa.com.
Want Samantha to present to your team or at your next event? Get in touch.