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Somebody on your team is uneasy about AI. You asked why, got an answer that sounded a little thin, and let it go. Sheryl Barbosa does not have that option. She is an environmental scientist and a sitting city council member, which means when a data center goes up outside of town, the neighbors bring her their fears. Her job is sorting the concerns that hold up from the ones that quietly stopped being true, and then talking to people about it without telling them they are wrong. In this conversation with Erik Martinez she covers what has actually changed about data centers, water, and power inside the last year, and why some of what all of us have been repeating is out of date. Then the episode turns. Erik could look up answers to the water question or the power question. But, there is no way to look up information about his own team, and he had been reading their AI hesitation as a verdict on the people rather than as the information it was. There is one question to ask your team, and how you frame it determines whether the answer that comes back is useful or worthless.

You've been using AI for months. You can see what it does. And when you look around the room, you can count on one hand the people on your team who are actually using it. The rest aren't pushing back. They just haven't started. "I had to hear from some other people how they're using it in their daily lives, and I didn't wanna just trust people who are tech-savvy." That's Mark Maynard, a coach, author, and speaker who helps leaders in hotels, restaurants, museums, and a construction company connect purpose to daily operations. Six months ago, he was the person on your team who still hasn't tried it. Using ChatGPT for recipes and road trip stops, nothing more. Mark joins host Erik Martinez on Episode 116 of the Digital Velocity Podcast to talk through what actually changed, and what it means for leaders trying to bring their teams along. Mark shares the specific moment a client problem broke through months of skepticism, explains why trusted people telling real stories mattered more than any demo, and describes how he used AI to help a construction company turn 1,000 pages of operational playbooks into something their employees would actually remember. "Efficiency was not the desired outcome, depth was." If the people on your team haven't bought in yet, this conversation reframes why, and what to do about it.

Tension-first. Functions as a trailer. The listener must hear the episode to get the answers. Jess Loseke spent 16 hours last weekend on her employee handbook. With AI. Your first question is probably the same as ours: why would that take 16 hours with AI? That is the wrong question. The right one is harder to sit with. "What is a pain to me are the things that are not getting done in my business because I cannot afford to hire for them. Those are the things that are killing the growth of my business right now." Jess Loseke, Co-founder, Midwest Barrel Company Jess co-founded Midwest Barrel Company, the first company to put a barrel (think Bourbon or Whiskey) on the internet. She runs lean, she's tech-forward, and she's ignoring the most common piece of AI advice right now. She's not starting with her most repetitive tasks. She's starting somewhere that, on the surface, sounds like the wrong place. Her business partner has a PhD. He's the best salesperson she's ever met. He sat down in a meeting and said, "I'm failing to see how I'm going to use this in sales." If a co-founder at an AI-forward company is saying that, what does it mean for the rest of us? Jess has an answer. It starts with a number: 75%. And it changes the math on what "good enough" means when the alternative is zero. This conversation with host Erik Martinez goes somewhere most AI conversations don't.

You are publishing more content than ever. So is everyone else. And somewhere in the rush to keep up, a lot of it started to sound the same. David Ebner, President of The Content Workshop, has a blunt explanation for why. "A tool doesn't know what good is." In this episode of the Digital Velocity Podcast, host Erik Martinez and David Ebner get into storytelling in the age of AI: why so much of it reads like word salad, what actually separates good from generic, and why the speed everyone is chasing might be the very thing making the work worse. David has spent 13 years telling brand stories, and he does not think AI is the problem. He thinks the problem is that most people never learned what good looks like before they handed the work to a machine. There is a specific thing David does before he ever hits the magic button that most people skip. Miss it and you get slop at volume. Get it right and the tool starts turning you into something closer to a superhuman writer. Listen to Episode 114 to hear where human creativity has to stay in the process, and why good was always good no matter how it gets made.

Erik Martinez and Pat Barry made their AI predictions six months ago. Agents, AI shopping, rising costs, governance. They were right about almost all of it, and almost none of it showed up the way they expected. Pat keeps running into the same pattern across every organization he works with. Someone has quietly built something remarkable with AI. When Pat tells them to share it, the answer is always some version of "yeah, they're not really into it." The capability exists. It's invisible. And nobody is asking why it stays that way. Meanwhile, Erik went from spending his days in Excel, PowerPoint, and Canva to doing ninety percent of his work inside tools that didn't exist in their current form six months ago. Pat's building entire training decks with agents that get him 85% of the way there in a quarter of the time. AI platforms are turning into the new office suite, and most people haven't realized the shift already happened. Token costs are climbing and Erik describes trying to track them as "absolutely maddening." One of Pat's healthcare clients made a governance decision that positioned them as what Pat calls "the team of the future." A university with 50,000 employees and access to the same tools can't keep up. The predictions were about what AI would do. What actually changed was how the humans work. That gap is the conversation in Episode 113.

Most agencies have someone who's figured out AI better than anyone else on the team. They built the custom GPTs. They know the prompts. They're the one everyone asks when something breaks. Now ask yourself: what happens if that person leaves tomorrow? "If your agency relies completely on one AI champion, the agency's progress is limited to one resignation." Ishant Kulshreshtha, AI Strategic Analyst at White Label IQ, joins host Erik Martinez on Episode 112 of the Digital Velocity Podcast to talk about what it actually takes to move AI knowledge out of one person's head and into the organization. Ishant shares a practical 30-day process any agency owner can start today, explains why the data your agency has been collecting for years is more valuable than any tool you could buy, and makes the case for why building AI capability is a team sport, not a solo act. If you've been relying on one person to drive your AI progress, this is the episode where you find out what you're actually risking.

579 agency leaders were asked what they need to do to succeed. The answers were clear. Then they were asked if they're doing it. 83% aren't. Brian Gerstner, president of White Label IQ and co-founder of Agency Core, sits down with host Erik Martinez to unpack what the Agency Core 2026 research found when it studied the gap between knowing and doing across small and mid-sized agencies. As Brian puts it: "there was very clear understanding of what needs to be done. And when we ask people, what are you doing? massive gap" The research identified three mindsets shaping the industry right now. One group is pulling ahead. The other two are either moving fast without a clear destination or stuck and overwhelmed. The difference between them is not what they know. Brian has a specific prescription for every agency still stuck in that gap, and it starts with something most agency leaders have been putting off.

The headlines say AI is changing everything about how businesses get found online. Cameron LiButti says those headlines are missing the point. Cameron is the founder of Bidview Marketing, a fourteen-person agency working with medical practices, law firms, and service businesses across the country. He spent four years as a mechanical engineer before finding his way into digital marketing, and that engineering background shapes how he approaches SEO: start with the data, build the structure, and be willing to tell clients what they don't want to hear. In this episode, Erik Martinez and Cameron work through what's actually happening inside search — and what isn't. AI Overviews aren't a new algorithm; they're a new interface sitting on top of machine learning that's been running since 2015. LLMs like ChatGPT aren't pulling from an independent database; they're scraping the web and Google's results. And the businesses that tried to game that system in 2024 are seeing the consequences now. The conversation covers: •          Why Cameron's answer to the most important SEO question hasn't changed in eight years •          How search intent determines whether AI is sending your prospects to you or past you •          What a tax attorney and a medical practice reveal about where AI leads actually come from •          The site structure fundamentals that apply equally to traditional crawlers and AI crawlers •          Red flags to watch for when evaluating an SEO agency or consultant

There's no agreed definition of an AI agent yet. The people building them, the people selling them, and the people writing about them all mean different things by the term. There's also a real disagreement about how to start. The conventional wisdom is to pick a small task and let an agent take it off your plate. That's not wrong. But the small thing you pick should be doing real work for you, or building a real skill you'll need later. Otherwise you're using AI to look busy. Pat Barry and Erik Martinez sit down to work through both questions. Pat, a data scientist and AI consultant, opens with the version of the agent definition he's heard most often: a client who literally meant a robot. From there they get into what actually counts, what doesn't, and where most of us should start if we're being honest with ourselves. If you've ever asked yourself whether what you're already doing counts, or whether the next thing you build is worth building, this is the one to listen to. In this episode: ·         Why nobody in the AI world has settled on what an "agent" actually is ·         What counts as one (and why what you're already doing might already qualify) ·         The simple test for whether the agent you're about to build is worth building

Most of us are using AI to solve a problem once. We polish an email. We summarize a document. We move on. And we tell ourselves we are getting good at this. Wes Lemos has been at this longer than most. He runs Roll Digital, founded TIV AI and Vibe Scribe, and has built hundreds of projects across multiple servers. In Episode 108, he sits down with Erik Martinez to talk about why solving a problem once is the entry point, not the destination. "One person with AI could do more work than a whole team can." There is a shift Wes describes that most people have not made yet. It's about what you do after AI gives you the answer the first time. Wes has a framework for what that looks like, and most listeners have yet to move beyond the first level of it. In this conversation, Wes and host Erik Martinez get into what is actually possible right now, why the gap between awareness and capability is widening, and the one shift that takes you from getting value out of AI to building real assets with it.

Ryan Shenefelt, digital marketing and AI innovation lead at deNovo Marketing, has been in this work for 13 years. Over that time he's watched what happens when agencies and marketing teams use AI the way most people use it: to confirm what they already think, to move faster, to check the box.   In Episode 107 of the Digital Velocity Podcast, Ryan shares a different approach. He uses AI to argue against himself. When he has a hunch about a decision, he tells the tool where he's leaning and then asks for every reason he's wrong. He separates the "why" and the "why not" into two distinct prompts so the AI fully commits to each side rather than hedging both at once.   This episode covers: ●        How to use AI as a contrarian thought partner when evaluating marketing strategy ●        Why synthetic panels and persona-based focus groups can surface blind spots in a plan before money is spent ●        The case for stopping new tool evaluation and mastering what you already have ●        How Notebook LM reduces the risk of hallucinations by keeping AI grounded in your own data ●        Using AI as a leadership coach to tailor communication across different personality types on your team ●        What "vibe coding" made possible for someone with a limited development background   "I will straight up tell it, I'm thinking this. Why not? Give me five reasons. Give me 10 reasons why not. And it's doing that gut check. It's telling me okay, you think this, what about this?"   Ryan and Erik Martinez also discuss the practical reality of building AI capability inside an agency: why it takes longer than expected to start, how to identify the recurring tasks worth automating, and what it actually feels like to spend 10 hours on something that saves you 15 minutes, and why that's still worth doing.   Ryan Shenefelt is the digital marketing and AI innovation lead at de Novo Marketing. He leads the agency's AI task force and works across account management, digital advertising, and strategy.

What would happen if you had a version of yourself available every morning that already knew your values, your blind spots, and the two or three things that actually need your attention today?   In Episode 106 of the Digital Velocity Podcast, Erik Martinez sits down with Joe Newberry, founder of ExecClone.com, to explore how AI is changing the way high-functioning leaders work. Joe brings a background in tech, finance, and sales leadership to a practical question most business owners avoid asking out loud: how much of what I do every day actually requires me?   Joe tracked his own time and behaviors down to the minute across a 30-day period and found he was only hitting his top three strategic priorities about 40% of the time. The remaining 60% was consumed by what he calls the urgent box, fires, repetitive input requests, and administrative tasks that did not require his level of experience. That data became the foundation for Exec Clone.   The conversation covers the core concept of building an AI "clone" as a leadership tool, including how the True Mirror operating system onboards a user with over 150 personality and values-based questions to create a digital Chief of Staff anchored in who you are and who you are trying to become. Erik and Joe discuss the difference between an AI that knows your most recent conversations and one that holds your past, present, and 10-year goals in memory at once. They explore the concept of emotional drift.   The episode also addresses data security and Joe walks through how ExecClone handles sensitive personal data differently than most cloud-based AI agents, including the option to run the system on encrypted hardware shipped directly to the client.   For agency owners and business leaders who are doing the work alongside their teams, this episode offers a grounded look at what it means to use AI not just as a productivity tool but as a real accountability partner.

What does an agency actually sell when AI can produce the work? That's the question driving this conversation, and Brian Gerstner has a clear answer. In Episode 105 of the Digital Velocity Podcast, host Erik Martinez sits down with Brian Gerstner, President and Owner of White Label IQ, an agency that works exclusively with other agencies. With over 25 years in the marketing industry, Brian brings a uniquely front-row perspective on how AI is reshaping the agency model and what it actually takes to stay relevant when the tools that used to make agencies valuable are now widely accessible to everyone. The conversation centers on a fundamental shift: AI has raised the baseline for what "good" looks like across marketing, making ordinary, production-focused work insufficient. As Brian puts it, "AI's just going to beat the mediocrity out of all of us." The real competitive advantage, he argues, is no longer the ability to produce deliverables. It is the ability to orchestrate them through what he calls a Personalized Data Layer: a documented, structured knowledge base that captures brand positioning, ideal customer profiles, product details, proof points, and brand voice. Key themes covered in this episode include: •      From tribal knowledge to documented scaffolding: Why relying on individuals to carry institutional knowledge is a structural risk, and how to replace it with a consistent, scalable system that survives personnel changes. •      The MVP of a Personalized Data Layer: Brand positioning, ICPs with real personalities and pain points, detailed product and service descriptions, testimonials and case studies, and a defined brand voice including what words to use and what to avoid. •      Why AI hasn't made work easier: "AI has not made anything easier. It's just made everything faster" — and that speed creates more volume, more threads to manage, and higher expectations across the board. •      The risk of AI slop: Without a documented knowledge layer to constrain outputs, AI will always generate an answer, but it will be generic, inconsistent, and trust-eroding for audiences who can spot it. •      Governance and accountability: How White Label IQ is implementing a matrix structure with pods and guilds, assigning document ownership, running 30-to-60-day verification cycles, and using EOS as a change management framework to hold leadership accountable. •      The human layer as the new premium: "If anything, AI is the thing that's gonna make us human again" — as trust in digital content erodes, showing up in person and maintaining real relationships becomes the differentiator AI cannot replicate.   While Brian's experience is rooted in the agency world, the implications extend to in-house marketing teams and brand leaders across industries, including direct-to-consumer businesses where audience trust, message consistency, and hyper-personalization are top priorities. As Erik notes, the average U.S. adult now receives over 8,000 messages per day, making the ability to reach and speak to a specific audience with precision not just valuable, but necessary. If you're a marketer, agency leader, or brand executive trying to figure out where to focus in an AI-saturated environment, this episode delivers a clear and practical answer: stop chasing tools and start documenting what makes your brand yours. As Brian says, "Without a backbone, you can't stand up." The strategic work of capturing your intellectual property, your positioning, your voice, your audience, is what will separate the agencies and brands that thrive in 2026 and beyond from those that get left behind producing generic output at scale.

In Episode 104 of the Digital Velocity Podcast, Pat Barry joins Erik Martinez for a fast-moving, practical conversation about how to build "individual capability with AI" as the foundation for stronger teams. Rather than treating AI like a one-time experiment, Erik and Pat focus on how capability is built through repetition, discipline, and real workflow reps (repetitions). Pat shares how his learning process evolved from "watching videos on YouTube" and "Googling stuff" to using LLMs like Gemini or Chat GPT for guided learning: "I just tell it what I wanna learn, and then I tell it, ask me more questions so I can, kind of tailor this to myself." A major theme is the reality of time constraints for marketers, agency leaders, and DTC operators juggling "a bajillion things on your plate." Pat breaks down how he makes progress anyway: "I use time boxing," and "I'll block off just an hour on my calendar," then stick to it. Erik ties the mindset back to coaching, reminding listeners that "you gotta do more reps" to actually improve, whether it's "short hops" at work or getting better outputs from AI. Listeners will learn: ·         How to use LLMs for guided learning by having them "ask me more questions" ·         Why "going and doing" beats passive consumption when AI changes constantly ·         How "time boxing" creates space to practice without adding chaos to your week ·         Why confidence is built through iteration and verification — not perfect first prompts ·         How individual capability becomes the bedrock for scaling AI across a team If you're leading a DTC brand, running an agency, or managing a marketing team, Episode 104 is a must-listen for anyone who wants AI adoption to translate into real execution — not tool overload. As Pat puts it, "You're never gonna start unless you start doing."

In Episode 103 of the Digital Velocity Podcast, Erik Martinez sits down with Kaitlyn Study, entrepreneur and owner of South Street and Co., to explore what it really means to move from experimenting with AI to fully operationalizing it inside your business. Over the past year, Kaitlyn has automated "250 plus tasks across her business," transforming repetitive processes into structured, strategic systems. As Erik frames it, this conversation is about "automating and operationalizing AI in your business, not the nuts and bolts of which buttons to click, but why this matters strategically and how it becomes a real competitive advantage." Kaitlyn's journey began with a simple realization: "How can I clone myself without using math and science?" After experiencing team turnover and the strain of repetitive operational work, she turned to tools like Zapier, N8N, and AI platforms to eliminate friction and create clarity. The result wasn't just time savings, it was precision. As Kaitlyn explains, "If the automation doesn't work, I know that I did something wrong and didn't correctly portray what I was trying to get out of it." That level of accountability changed how her agency manages hiring, time tracking, sales follow-ups, and capacity planning. Listeners will gain practical, cross-industry insights, including: ·         Why "auditing your time" is the first step toward meaningful automation ·         How to identify "friction" points that signal automation opportunities ·         Why "you have to test it and test it and test it" when integrating AI into workflows ·         How freeing "brain space" allows leaders to focus on higher-level strategic thinking ·         Why the goal "is not to replace people" but to "have you do better, higher level work that you're really great at" For direct-to-consumer brands, agencies, and growth-focused executives, this episode offers a roadmap for scaling operations without sacrificing creativity or culture. Automation, when applied thoughtfully, becomes evolution, not revolution. As Kaitlyn emphasizes, "The goal is not to replace people. It's to have you do better, higher level work that you're really great at, and to have the nuanced, repetitive tasks taken care of." If you're serious about turning AI from a tool into a competitive advantage, this episode is a must-listen.