Welcome to Search With Sean: Weekly Digital Marketing News. Your weekly breakdown of SEO, AI, digital marketing, and search trends shaping the industry right now.

Co-Hosts

Laura Iancu – https://www.linkedin.com/in/laura-iancu-seo/

Christian Goodrich - https://www.linkedin.com/in/cargoodrich/

In this week’s episode, we look into some of the most important shifts happening across AI, search, and digital marketing – from model safety concerns and enterprise AI risks, to Google’s aggressive push to bring Gemini into mainstream culture, and what that means for the future of search behaviour.

We start with a deep discussion around Claude’s latest model developments, including the contrast between “safer” public-facing versions like Fable and more advanced internal systems like Mythos. The conversation explores the growing gap between AI capability and public release constraints, and what that means for security, governance, and business risk.

From there, we move into one of the biggest underlying themes of the episode – AI security and organisational readiness. We discuss how quickly companies are adopting AI tools without clear guardrails, and how “vibe coding” and rapid AI-assisted development could introduce hidden vulnerabilities into live environments, from small businesses to enterprise SaaS platforms.

We also explore how different AI models are being used interchangeably across teams (Claude, ChatGPT, Gemini), and why lack of structured policy is becoming a major risk factor for data exposure and compliance issues.

Next, we look at Google’s marketing strategy for Gemini, including its high-visibility World Cup advertising campaign. This sparks a wider discussion around platform dominance, consumer behaviour, and whether AI adoption is now being driven less by choice and more by exposure at scale.

We then move into Google Discover’s new “search profiles” update, which gives publishers and creators a more structured way to present content across Google surfaces. We explore whether this could meaningfully shift visibility dynamics or if it risks repeating past experiments that failed to gain traction.

In the hiring and skills space, we break down findings from Moz research into the AI search skills employers actually want. Despite the AI hype, the data shows that traditional SEO fundamentals, analytics, and measurement still dominate hiring requirements, with AI skills acting as a supplement rather than a replacement.

We also explore what this means for professionals trying to demonstrate AI capability on CVs, and how real-world application (automation, tooling, measurable outcomes) is becoming more valuable than surface-level buzzwords.

The episode then moves into a broader industry debate around publishers and AI training data, including the growing pushback against scraping via systems like Common Crawl. We discuss the tension between content creators, platforms, and AI systems, and whether new licensing or control frameworks are inevitable.

Finally, we reflect on the wider implications of AI adoption – including concerns around AI-generated content quality (“AI slop”), sustainability, carbon footprint, and whether the industry is moving faster than its ability to regulate, secure, and responsibly scale these systems.

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