Are not enough people using agentic workflows, leaving the market open? Can you give an example of the distribution bottleneck?
Most people see AI as a simple chatbot that answers questions like a search engine, not realizing it can be woven into a business’s core infrastructure—such as decision‑making routing—to act more like an intelligence that moves information through a network to solve problems faster. Over the next few years, companies that implement AI infrastructurally will see major gains in speed to market, customer‑need identification, and product development. For example, when I posted a job for packaging and ideation, applicants didn’t send simple pitch ideas; they built full applications showing how my YouTube titles and thumbnails would look with real‑time data, demonstrating how deeply AI can surface and address user needs.
You can apply this to virtually any business on Earth. If you ask them to walk you through their customer journey from first contact to last, even a monkey could see where AI or automation could help. The core problem today is that we can model these automations but they often produce no intended output—it's just raw image knowledge. If you get on a call with one of these people, watch five minutes of any of my videos, see what they're doing, and you'll immediately think, 'Okay, we can actually improve this significantly, or even reach Einstein-level insight.' That's how it is: most business owners lack the time to watch YouTube videos like we do, or to write out pipelines and similar processes. Getting on a call with you makes it a simple process, yet you'll be surprised how many high‑performing businesses still send most of their emails manually, copy‑paste templates, or rely on administrators who just enter data into standardized government forms—they haven't realized this capability yet. While it's not a complete fix, you can exploit the current market arbitrage by learning just enough to frontload outreach and articulate these solutions, thereby building a strong distribution network. In 5, 10, or 20 years, depending on the economy, that network could survive because clients prefer working with you due to lower friction and ease. In short, distribution is crucial. As an example, Zed started outreach with a low‑level Instantly clone for his own use, sending 15 emails a day limited by one inbox, and couldn't find good free PPC agency communities for real conversation. My recommendation: if you're 15 or 16, get paid inboxes via a platform like Instantly—they've already done the work you're doing, so you can exchange a small fee for immediate scale without rebuilding everything from scratch. It really does make sense.
The vast majority of those elaborate AI‑agent flows you see online are just for views—they don’t actually make money because the agents aren’t reliable enough to do real work. Businesses don’t want a model that can answer in a million different ways; they want a highly constrained output—maybe just five or six possible answers—so they can control most of the content. What they really want is for you to scrape a resource, run it through an LLM API to get a few rephrased versions (like icebreakers or paraphrased job titles), and then slot those into a templated email or document. The LLM fills in only the small, variable pieces while the rest stays fixed, giving them control and reducing unpredictability. In short, treat LLMs as APIs rather than autonomous agents; that’s where the money is right now.
High ticket is going to be tough here, but there are some simple AI-enabled services you could sell to online coaches like myself. One is need determination: if they run big communities, have a big brand, or get lots of YouTube comments, you can quickly build systems that scan everything customers are asking about, unclear on, or explicitly asking for videos on, and turn that into content. It usually surfaces very interesting insights most people miss. You can also build an "ask a question" funnel into the coach's inbound flow, or just tell people at the end of content to leave a comment. I pick what content to do next almost entirely based on your comments. How do I know this works? Because that's what I do, and I built the system myself. You wouldn't believe how many brands ask me what my packaging and ideation flow is, and the answer is I usually start with questions my customers ask me. Beyond that, you can use AI to shorten the time it takes to reach out to someone interested in a high-ticket offer, say $1,000 to $5,000 a month with four or five months of average churn, which might be worth $20,000. The usual flow is ads, PPC or organic to a landing page with a book-a-call funnel, setters reaching out to book the appointment and maximize show rate, then the closer on the call. You can use AI to automate a large portion of that, cut speed to lead, improve the quality of the conversations through intelligent automated replies, and automate the follow-ups.
The best way to implement AI in a digital business is not to start with the back‑office tasks like fulfillment, accounting, HR, or other tedious, time‑intensive processes. Those are low‑value automation opportunities that only save you money you already make. Instead, focus AI on the front‑end of the business – growth, reach, acquisition, conversion, and lifetime‑value expansion. Think of AI as a tool that helps you get more impressions, improve ad and organic reach, boost conversion from eyeballs to leads, speed up payment systems, proposals, and follow‑ups, and ultimately increase upsells and product differentiation. One hour spent automating admin might net you $50, whereas one hour spent building a system that improves a company’s ability to grow could generate $5,000. Even with modest margins, that’s a 25× multiple. So prioritize AI projects that directly impact revenue generation rather than pure cost‑cutting.