Conversational AI meets cognitive bias: Re-engineering search strategy for the human brain

Don’t Dump LLM Visibility on Your SEO Team

Here’s an uncomfortable conversation no one wants to have with their CMO. When AI visibility became the next big metric to chase, most marketing leadership did what felt instinctively logical: handed it to the SEO team. Rankings, citations, mentions — that’s what SEOs do, right? Wrong instinct. And in this episode, Miruna explains exactly why. LLM visibility isn’t a ranking problem. It’s a brand perception problem. When you audit why your company isn’t being cited by AI, what you often don’t find isn’t a technical gap — it’s a positioning gap. A signal that the market doesn’t fully understand who you are, what you’re best at, or why you matter. That’s not something an SEO team fixes with an outreach campaign and a few listicles. That’s a CMO problem. Or — as Mordy points out — a CEO problem, because the CMO is usually just absorbing pressure from above. Miruna shares a candid example from Planable’s own experience: their LLM audit didn’t reveal a citation problem. It revealed that the market still perceived them as a niche collaboration tool, not the fully equipped platform they’d since become. The SEO team was never supposed to fix that. It was always a brand repositioning conversation that no one had escalated to the right level. Laura Little, founder of the British Chick Marketing Agency, joins to answer the question that makes a lot of org charts uncomfortable: if LLM visibility is just a symptom of brand visibility, then who should actually own it?

You have to be crazy to advertise on ChatGPT!

Short answer: yes. Long answer: this episode. ChatGPT is running ads at $60 per impression. Not per click — per impression. That’s Super Bowl money, for a platform where the majority of users still aren’t seeing any ads, you have almost no visibility into who you’re reaching, and the audience came specifically for an answer — not an ad. Mordy and Miruna break down why this feels less like a media buy and more like a fundraising mechanism for OpenAI’s investors — and why the brands currently signing up tend to be the AT&Ts of the world, not the Verizons. Second-tier players in their categories spending Super Bowl budgets for approximately none of the Super Bowl upside. The bigger point: if your brand isn’t showing up in AI results organically, an ad won’t fix that. It’s a brand problem, not a budget problem — and the solution is building the kind of presence that AI wants to mention without being paid to. Jordan Koene, founder of Previsible and host of the Voices of Search podcast, joins to talk about exactly what that looks like in practice.

Stop Using AI for Output — Use It as Your Audience

“How much more can we produce with AI?” is the wrong question. Everyone is measuring AI adoption by output: more content, more copy, more campaigns, more. Mordy Oberstein and Miruna Dragomir argue that framing has teams convinced they’re getting value from AI when they’re actually getting the least interesting thing from it. The smarter move? Use it as your audience. Miruna built a custom GPT trained on her brand’s target personas — not to generate content, but to push back on it. The AI’s job wasn’t to help. It was to simulate a skeptical reader and flag where the messaging wasn’t landing. The result? More useful than any creative brief. From stress-testing a strategy pitch against a simulated CEO to understanding how LLMs reflect internet-wide perception of your brand, this episode makes the case that AI’s real value isn’t in the output it produces — it’s in the thinking it forces. Amanda Natividad, VP of Marketing at SparkToro, joins with her own take on using AI for audience research and strategic input rather than task automation.

[Debate] Budgeting for multi-engine search: Where should your next $10K go?

At SEO Foresight 2026 on December 9, join widely respected voices in search—Barry Schwartz, Melissa Popp, Erin Sparks and Grace Frohlich—for a grounded discussion on how teams are planning budgets across today’s multi-engine landscape.  With Google’s AI Mode reshaping results and “answer engines” gaining traction, this session compares real-world approaches without one-size-fits-all prescriptions. What’s on the agenda? * Ways teams prioritize among content, citations/PR, technical work, and partnerships/data—plus common trade-offs. * What “impact” can mean in 2026: inclusion in AI answers, citation quality, and durable brand visibility. * Practical considerations for planning and measurement across multiple surfaces (no one-size-fits-all). Join to hear different perspectives and gather ideas for your own 2026 discussions. Grab your free seat now.

Multi-platform search is here: Building brand visibility across Google, TikTok, and answer engines

Join Jessica Redman, co-founder of Didgeheads and multi-platform visibility strategist, for a fast-paced guide to showing up across Google, TikTok, and AI answer engines. In this episode, Jessica unpacks the psychology behind today’s multi-touch search journeys and shares playbooks for earning inclusion in quick answers (AI Overviews, Copilot, Perplexity), building TikTok-native discoverability, and structuring catalogs so people and machines find products faster.  You’ll learn how to clarify entities, use structured evidence, and turn long-form content into short, searchable video—plus what to track when clicks are scarce: share of voice, citations, assisted conversions. We also touch on answer-led browsing and new data-sharing rules that keep Chrome intact—and what they mean for channel mix and measurement. Planning portable brand visibility in 2025? Start here.