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.