AI Marketing

Host: Mark Fidelman Guest: Julian Goldie Main Topics Covered: The rapid evolution of SEO in the age of AI How AI tools like ChatGPT, Perplexity, and Grok are changing online search behaviors Similarities and key differences between traditional SEO and optimization for AI search engines Importance of being omnipresent across platforms (YouTube, LinkedIn, Reddit, blogs, etc.) for better AI engine ranking Essential tactics: in-depth keyword research (using tools like Ahrefs), competitor analysis, content strategy, and authoritative backlinks Special techniques such as creating industry listicles to boost authority Discussion on ChatGPT's "Agent mode," its potential impact on search, and the importance of structuring information for both users and AI agents Predictions for the future: the increasing role of large language models (LLMs) like ChatGPT in search, and how Google is rapidly integrating AI into its own results Budgeting advice for marketers: integrate SEO and "AEO" (AI engine optimization), focusing on an all-encompassing strategy Action Items: Follow up with Julian for deeper insights into AI agent modes and evolving tactics Use Ahrefs for ongoing keyword research Reverse-engineer and improve upon competitor content Focus on acquiring industry-relevant backlinks Experiment with authoritative list-based content Guest Contact: Julian Goldie, SEO specialist. Visit JulianGoldie.com for a free SEO strategy session and more resources

In this episode, host Mark Fidelman is joined by Jon Mest from ChatRank to discuss how brands can prepare for the fast-approaching era of AI-driven discovery and agentic systems. The conversation covers: The evolution of brand discoverability, with a look ahead to how AI language models and agents will change how consumers find and interact with businesses. The concept, benefits, and future of AI-only websites, and how they differ from traditional, human-oriented sites. Why structured, well-tagged product information and content is critical for visibility within AI systems. The growing importance of authentic social proof—such as customer reviews, forums, and third-party ratings—to boost a brand's credibility with AI agents. How brands can leverage video, podcasts, and other multimedia content to increase discoverability and connect with both AI systems and human audiences. Actionable strategies for preparing your brand for AI-driven search, including building a strong presence on platforms like YouTube, Reddit, and industry-specific review sites. Insights into how brands can stand out with unique, novel information and real customer feedback as competition increases with the proliferation of AI tools. ChatRank's role in helping businesses audit, track, and optimize their brand presence for AI discoverability, including both self-serve software and managed services. Key Takeaways: Start exploring AI-only websites tailored for agentic interactions. Make your product information highly structured and accessible to AI. Develop a comprehensive strategy to build authentic social proof. Invest in video, podcasts, and other easily digestible content formats. Learn how to get your brand ready for the new world of agentic discovery with practical advice from www.ChatRank.ai , and visit chatrank.ai for more information. Follow the host mark @markfidelman Get Mark's book at www.agentized.com

Show Notes: Know What to Think Episode length: ~41 minutes Chapters (Skip Ahead) 00:00 — Know · What · Where · Artificial. It's really entertaining, and we're doing a lot of fun, good stuff. Then, maybe… maybe longer, but let's just see how it goes. Most are between 10 and 20 minutes. Alright, go ahead and start. Yep, I'm gonna hit the… 05:00 — There · Robot · Know · What. Right, okay. Alright, so why… why isn't nuclear an option to bring the kind of power we need? Yeah, I mean, I think the short answer is it's available, it's accessible, but I don't think it's enough to actually solve… 10:00 — Don't · Know · They're · More. It's a $200,000 vehicle at a minimum, if not $250,000. I don't know how that thing makes money. To be honest, I mean, does anybody think it— a taxi driver driving a $200,000 car—can… quickly… money on a regular basis.… 15:00 — Know · What · You're · I'm. I'm gonna… you know, what we can actually do with that, I don't really know. I feel like, you know, we've… we know what… the powder that produces dynamite, but the problem is that we don't have any casing, and… 20:00 — Its · Own · Why · Think. …even abnormally distributed. And this is really normal with past types of dimensions, with electricity and airplanes, or even the combustion engine for cars, etc. But at the moment, right now, you know, we really need… 25:00 — Know · What · Don't · Why. The question is, why? We already have enough of us. Yeah, I mean, you know, maybe we need less of us, I don't know. It depends—depends on your opinion, I guess. Well, but for me, you said it correctly: what is our goal… 30:00 — Know · Quite · Think · Mean. There's quite a number of individuals like that in Silicon Valley. And that's been true. He's tried to sue Sam Altman afterwards to become a founder. He was not actually the original founder of Tesla; he sued his way… 35:00 — Know · Things · One · Human. You know, the math is… it's… it's gnarly. It's hard, and yeah. So we need a lot of power for this. Isn't it interesting, though, that one human being—powered by food and the sun—can do exactly what… 40:00 — Good · Maybe · Time · Fun. Follow me next time. Yeah, maybe next time we'll talk about that. Fantastic conversation. There are other things coming up that I'd love to get you on—your perspective. I love your angle, it's… Notable Quotes And I think that… ultimately, I don't know, maybe people watch too many movies; they think those movies are reflective of what we're gonna see in the future. Artificial intelligence—if it was a car and you open up the hood—what do you see? I think artificial general intelligence… let me map out, ultimately, what you're trying to ask here. And here's the reason: artificial intelligence… there's always errors. I don't agree, and I don't think it's gonna be Skynet; I don't think it's gonna be I, Robot. I mean, they're entertaining. But I'm also a realist; I know that a lot of this is hype—but it's fun, it's fun. There's a lot of things that we have as artificial intelligence right now that we use. I feel like we know the powder that produces dynamite, but the problem is we don't have any casing—and that's where we are right now.

Guest: Mariano Garcia-Valiño — engineer and healthcare founder (3 exits; now building his fourth) Episode Summary Healthcare is burning cash and patience. Mariano lays out a blunt playbook: aggregate real-world signals (labs, pharmacy fills, wearables—even spending patterns that hint at adherence), run AI to flag risk early, and route people to care before conditions explode in cost. No sci-fi. No diagnosis claims. Just practical prediction, consent-driven data, and measurable outcomes. Key Takeaways Cost crisis ≠ destiny: US costs outpace inflation; prevention and earlier intervention are the only scalable fix. Data > drama: EHRs + labs + pharmacy + wearables + behavioral/financial breadcrumbs create a far clearer risk picture than any single stream. AI's role today: Triage and risk flags—not final diagnoses. Models surface "high suspicion" and hand off to clinicians. Privacy is the moat: Strict consent, separation from employers/insurers, and legal walls keep PHI protected and trust intact. What signals matter: From basic blood panels and pharmacy gaps to face-scan metabolic cues—more signals = better precision. Why consumers care: Earlier answers, fewer nasty surprises, and lower lifetime spend. Prevention is the new ROI. Business model reality: Think subscription + outcomes, not one-off tests. The value is longitudinal. Chapters & Timestamps 00:00 — Why AI in healthcare actually matters now 00:34 — Meet Mariano: engineer → serial healthcare founder 06:08 — The cost curve problem and why prevention is unavoidable 07:44 — What this company really does: navigation + prediction, not diagnosis 08:01 — Remote monitoring basics: from wearables to at-home capture 09:13 — The messy truth: fragmented data, privacy laws, and integration 12:19 — How data flows in (and why employers never see it) 13:39 — Why financial/behavioral signals boost predictive power 18:13 — What AI tells you: ranges, suspicions, and next clinical steps 19:29 — The "why now" for consumers: earlier lifestyle change, lower costs 21:10 — Roadmap & what has to be true for this to scale Notable Quotes "We raise a flag, then route you to the right clinician. That's how AI actually saves money today." "If you stop filling your medication three months in, the model will catch it—and that's the moment to intervene." "Prediction beats reaction. Every time." Practical Uses (Mark's Playbook) Health plans & clinics: embed risk-flag APIs into care navigation and care-gap workflows. Employers: fund prevention programs without ever touching employee PHI—measure outcomes only. Startups: focus on data rights + consent UX; it's the difference between demo-ware and deployment. Call to Action If you're building AI for real people—not hype subscribe to AI Marketing, and DM me on X/LinkedIn @markfidelman If you want the executive playbook on AI agents, join the waitlist at Agentized.com

Humanoid robots just jumped from sci-fi to go-to-market. We unpack Neo from 1X—what it is, what it can (and can't) do today, and how humanoids will reshape marketing, service design, content, and consumer behavior. We also hit privacy, regulation, price, and competition (Tesla Optimus, Boston Dynamics). If you sell to consumers or operate storefronts/hospitality, this is your early warning—and first-mover playbook. Humanoid Robots in Marketing Neo Humanoid Robot Overview Key takeaways (for marketers & founders) New channel: the robot at home. Neo is effectively a walking, talking, context-aware device that can surface highly personalized offers ("I see Folgers—want their new roast sample?") — powerful but must be transparent/opt-in to avoid creepiness. Humanoid Robots in Marketing "Robot Optimization" will follow SEO. Expect brands to build "skills" for humanoids (folding, cooking, demos) and fight to be the default skill for a task. App-store dynamics are inevitable. Humanoid Robots in Marketing Neo Humanoid Robot Overview Novelty marketing works—briefly. Pepper/Connie-style deployments boosted foot traffic and attention; humanoids will 10x the experiential angle, but you'll need real utility to sustain it. Hotelier Magazine+4Vox+4Emerj Artificial Intelligence Research+4 Costs & limits mean B2B first. With $20,000 or $499/mo and first US deliveries slated for 2026, near-term impact skews toward shared environments (hotels, banks, quick-serve, pop-ups) vs. mass consumer homes. 1X+1 Reality check. Expect tele-ops "expert mode," battery and dexterity constraints, and privacy guardrails early on. Treat Gen-1 as a marketing and service pilot platform, not a labor panacea. Neo Humanoid Robot Overview 1X Competitive heat. Tesla Optimus is improving fast (but still looks clunky in public demos); Boston Dynamics pushes manipulation and mobility. Plan for rapid capability jumps through 2026–2028. Cinco Días Neo Humanoid Robot Overview Suggested chapter markers 00:00 – Why humanoids matter for marketers (new touchpoint, personalization) Humanoid Robots in Marketing 04:30 – Use cases: retail, hospitality, pop-ups, content (robot concierge, robot "spokes-creator") Humanoid Robots in Marketing 10:10 – The "Robot App Store" & skill economics (default skills = moats) Humanoid Robots in Marketing Neo Humanoid Robot Overview 13:40 – Data, ethics, and transparency (trust > conversion) Humanoid Robots in Marketing 16:45 – Constraints: cost, batteries, tele-ops (pilot smart, don't overpromise) Neo Humanoid Robot Overview 19:30 – Competitors & timelines (Optimus, Atlas; what to watch) Neo Humanoid Robot Overview 21:30 – Mark's playbook & call to action Humanoid Robots in Marketing Mark's take (no fluff) Early humanoids are a marketing weapon disguised as labor automation. Use Neo-class robots to earn attention, collect consented preferences, and deliver "wow-utility" in the real world. If you wait for Gen-3 perfection, your competitor will already own the default robot skill for your category. Humanoid Robots in Marketing Neo Humanoid Robot Overview Episode receipts & references (watch/read these) Official NEO pages (pricing, delivery, FAQ, deposit): preorder $20,000 early access or $499/mo; US deliveries 2026; global expansion 2027. 1X+21X+2 1X company background (Halodi → 1X; EVE → NEO): history, founders, and industrial lineage. 1X+2Robots Guide+2 IShowSpeed x NEO livestream (earned-media case): viral, chaotic, and effective. YouTube+3YouTube+3Humanoids Daily+3 Precedents for robots in service/retail: Pepper raised foot traffic/sales in pilots. Vox+1 Hilton "Connie" (Watson-powered concierge) set the hospitality precedent. IBM UK Newsroom+2The Verge+2 Competitor snapshots: Tesla Optimus recent demo and scale ambitions. Cinco Días Boston Dynamics / Atlas (manipulation & mobility trajectory). (Mentioned contextually in episode.) Neo Humanoid Robot Overview Spec-style write-ups: quick primers on NEO dimensions and hand DOF. Humanoid Guide Practical next steps (for listeners) Pilot a "Robot Host" in one location (hotel, showroom, flagship retail). KPI = qualified footfall, dwell time, opt-in rate. Humanoid Robots in Marketing Design one signature "skill." Own a mundane, high-frequency task (fold, greet, demo) and brand it—become the default. Humanoid Robots in Marketing Consent-first data loop. Use the novelty to win explicit opt-ins; return value via hyper-personalized service, not ads. Humanoid Robots in Marketing Budget realistically. Treat 2026 as paid R&D: hardware + staff training + content capture. (Yes, film everything.) Neo Humanoid Robot Overview