The foundation of this conversation rests on what Sam calls the "AI slop paradox"—the counterintuitive reality that the flood of mediocre AI-generated content has actually made strong ideas and compelling messaging more valuable, not less. People come to the internet already skeptical, already believing there's AI slop everywhere. Whether or not that's objectively true doesn't matter—the perception exists. So when people encounter messaging that's genuinely compelling, ideas that are clear and specific and rooted in a point of view, they pay more attention to it than they would have before AI. The lesson here isn't that AI makes creativity obsolete. It's that creativity—the ability to conceive of something, articulate it clearly, and communicate it with conviction—is still the only thing that converts. AI can help you refine and express your ideas faster, but the idea itself still matters more than ever. Sam's entry into AI wasn't through a computer science degree or a tech accelerator. In late 2015, while working on a conversion rate optimization project with an Amazon team, he met a machine learning scientist who casually mentioned that models would soon be able to predict text the same way they could predict numbers. That planted the seed. Sam started researching, diving into papers on machine learning and transformer architecture, trying to understand where this was heading. By 2019, he had early access to GPT-2 and immediately started testing it with clients. He fed the model prompts for Google ads—very short form, character-limited copy—and then ran those ads without any human editing. They converted as well as human-written copy. That was his zero-to-one moment. If GPT-2 could write ads that converted, where would GPT-3 go? Where would GPT-4 go? The trajectory was clear, and Sam positioned himself to ride it. But Sam didn't stay in the copywriting lane. He realized early that the bottleneck for improving conversions isn't copy—it's the system around the copy. You can have a world-class copywriter write a landing page that increases conversions by 50%, but if there's no follow-up system to maximize the value of those leads, it doesn't matter. At the end of the day, a business doesn't need more conversions. It needs high-quality customers who buy repeatedly over time. That requires a full view of the customer journey—who's coming to the page, what happens after they convert, how you nurture them, how you retain them. This systems thinking approach is what led Sam to transition from copywriter to Fractional Chief AI Officer. He started seeing AI not as a better writer, but as intelligence that could be embedded across entire business functions to optimize outcomes at scale. When Sam started building AI systems for clients in 2020, he couldn't call it "AI" because people had sci-fi images in their heads—killer robots, super-intelligent systems that know everything. Even "machine learning" was too abstract for most business leaders. So he positioned his work as "systems for outcomes." Clients would come to him saying their sales process was broken or stagnant. Sam would look at the full system—where does this start (prospecting, traffic acquisition), and where does it end (closed deal, retained customer). Most of the time, companies didn't even have a system. They just had a wonky process. Sam would transform that into a system—a mixture of automation, AI, and humans at different stages—designed to deliver specific business outcomes. The key to his positioning: he didn't say "we'll build you a sales system." That's too generic, too wide, and not worth anything. Instead: "We'll optimize and maximize your existing sales process to convert more leads into sales-qualified leads who become high-ticket, high-value opportunities for your business." Now that's clear. That's specific. That's an outcome. The biggest misconception companies have about AI for marketing and copywriting? They've watched too many demos and been sold too many shiny objects by overnight AI gurus. They see a demo and think it's a finished, deployable product. They've been promised that prompts will make them millions, that agents will do all the work, that you press a button and money comes out. The same old opportunity mindset repackaged for the AI era. What they don't understand: AI only works well if you bring something to the table—data, information, context, examples. And most businesses don't have good data management. If they're capturing data at all (which isn't common), it's not handled or structured in the right way. So when Sam works with companies who want him to build AI systems, the first step is always fixing their data infrastructure. It's not sexy. It's not the shiny object. But it's the foundation that makes everything else possible. When deciding what to automate and what to keep human, Sam uses a simple framework: cost analysis. How much time, labor, and energy does this process cost you right now? If you automate it fully, how much will you save and how long until you break even? What if you do a hybrid model with AI and humans? What if you keep it fully human? Sam presents clients with three options and the math behind each one, then lets them decide based on their risk tolerance and business priorities. Interestingly, 99 out of 100 companies want a human in the loop. Very few are willing to let AI handle everything, except for small tasks like document processing or data entry. Sam predicts this will shift gradually as people become more comfortable, but right now, most businesses aren't ready to hand full control to AI. Sam's blunt take on AI for copywriting: Claude 4 Sonnet can write excellent copy that converts as well as a human copywriter, sometimes better. And you don't need to be an expert prompt engineer to get it to work. You just need to give it good examples and context—which means you need to have examples to give it. If you're an experienced copywriter who understands persuasion and knows what good looks like, you can get AI to write autonomously and it will perform. If you're a junior copywriter or someone who doesn't understand online persuasion, you'll struggle because you won't know how to guide the model or evaluate the output. The real skill isn't prompting. It's communication, taste, judgment, and knowing what works. Good prompting is just good communication. Sam has been using synthetic research and AI personas for years, starting with machine learning models that simulated human behavior. Now he uses groups of 50 to 100+ AI agents to go through competitors' websites, click on their ads, follow their lead generation flows, and analyze their messaging and positioning. He even uses voice agents to call competitors' sales teams and have realistic conversations to see how they're positioning their product and handling objections. The voice agents are so good—low latency, natural-sounding voices—that salespeople can't tell they're AI. The only way you'd know is if you suspected it and asked trick questions. This creates a continuous competitive intelligence system that informs messaging, positioning, and strategy decisions in real time. It's not theoretical—Sam is doing this right now for clients. Sam's "living business" concept challenges the traditional factory model of business—rigid processes, standard operating procedures, mechanistic execution. The factory model isn't bad, but if you think about your business only through that lens, there's no room for intelligence or adaptability. Everything is just input, process, output. But if you think of your business as a living organism with its own intelligence, memory, and knowledge, suddenly there's space for AI to exist not as a tool you use, but as intelligence embedded inside the business itself. You don't have to be the one with all the knowledge—the business can have it. You can ask your business questions, surface insights, optimize processes, and identify opportunities in ways that weren't possible with a mechanistic mindset. This mental model shift unlocks more opportunities for growth, revenue, profit, and competitive advantage than the factory lens ever could. When asked about the future of copywriting, Sam says it's not doomed—but it will fragment. There won't be one future for copywriters. There will be many different futures for different types of copywriters. If you're a junior copywriter or mediocre at your craft, it's going to be tough. AI will eat your lunch. But if you're an experienced copywriter who understands persuasion, psychology, systems, and how to communicate value, you'll thrive. You'll use AI as a force multiplier. The differentiator won't be technical skill—it'll be taste, judgment, and the ability to have a strong point of view. Which, as Sam pointed out at the beginning, is exactly what cuts through the noise and converts. Whether you're a copywriter trying to figure out how AI fits into your work, a founder looking to build intelligent systems in your business, a marketer who wants to move beyond AI hype, or a strategist who wants to understand what actually works at the systems level, this episode offers practical frameworks, honest insights, and a clear-eyed view of where we are and where we're going. Enjoy! CONNECT WITH SAMLinkedIn X (Twitter)Bionic Business NewsletterSHOW NOTES02:33 Why Strong Ideas Cut Through the AI Content Flood05:33 Sam’s Origin Story: Amazon, ML, and Predicting Text08:53 The GPT-2 Wake-Up Call: AI-Written Ads That Convert10:07 From Copywriter to Fractional Chief AI Officer: Thinking in Systems14:45 Creativity, Brand vs Direct Response, and the “Big Idea”18:13 Prompting as Communication: The Tree of Talking Mental Model19:54 Selling AI Systems Early: Avoiding the ‘AI’ Label and Focusing on Outcomes22:21 Biggest AI Misconception: Shiny Demos Without Clean Data24:57 What to Automate vs Keep Human: Cost Analysis + Paid Discovery26:55 H
