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#212 · How to Completely Automate AI Agencies w/ Natural Language

youtube ↗AI & Automation

You said communicating with AI to solve business problems will be a highly leveraged skill, but since it's easy to learn, there will be lots of competition. What are your thoughts?

It's easy to get started with AI communication because the companies building these models intentionally make them accessible so anyone can get decent results without being a prompt engineering expert. However, the real advantage comes from skill: due to a power‑law relationship, improving your prompting ability from the 90th to the 99th percentile can roughly double the quality of the AI’s output. In other words, small gains in skill produce large gains in results. While the basics are simple, mastering AI prompting is hard, and because AI is a meta‑tool that enhances all other tools, becoming proficient at it makes you effective across many domains.

aiprompt engineeringskill

Related answers

youtube ↗Mindset

Rage Sheshvel says uh in your recent video you mentioned AI may not be that use a automations may not be that useful in 2026 2027. What skill sets should we master to survive and thrive in the automation and agency space during that time?

To survive and thrive in the automation and agency space in 2026‑2027, master business skills: learn to communicate business needs and requirements, speak in consulting terms, understand core consulting concepts like driver trees and a four‑step framework, grasp foundational business principles (revenue, cost, profit, valuations, risk conceptualization akin to an 80/20 view of a business degree), and then get in front of customers to practice selling and communicating—exactly what Maker School teaches.

business skillsconsultingdriver treesmaker school
youtube ↗AI & Automation

Can AI models create highly technical, personalized solutions for institutional clients, such as integrating into a firm’s tech stack?

I’m not an expert in crypto, but models will fail a lot—about 70% of the time. The goal isn’t to prevent failures but to make them happen quickly so we can learn. Models are highly parallelizable; you can spin up dozens, test many approaches, discard what doesn’t work, and feed the results into the next model. By iterating fast, you eventually get a solution that works for complex, technical use cases.

ai modelsautomationintegration
youtube ↗Marketing

What’s the best way to market AI‑driven learning, training, and onboarding services for new hires, and is there demand for them?

I haven’t sold anything in that space yet, but a good starting point is a knowledge‑based tutor like what Khan Academy is doing. Identify the transformation event – for example, when someone signs an employment contract – and then send an onboarding packet that includes AI‑powered educational content. You could provide an AI mentor chatbot trained on the company’s knowledge base, along with course modules that the new hire completes while using the AI assistant. Demand isn’t huge in the mid‑market; larger enterprises might see value because AI onboarding can cut HR costs by around 10%, potentially boosting margins. It’s mostly a spit‑ball idea, but enterprise could be the sweet spot.

ai educationonboardingenterprise
youtube ↗AI & Automation

What was the biggest lesson you learned in your hardest AI project on your AI journey?

The biggest lesson I learned is that the actual product or service you sell doesn’t matter much—AI automation is just a fulfillment mechanism. What really counts are the core business systems you build around it: lead handling, sales scripts, onboarding, admin, hiring, marketing, taxes, etc. Those pieces stay the same across industries; only the specific service you deliver changes. Once you have a solid business foundation, you can swap in any offering and still succeed. I’ve seen the same principles work when I sold videography, local SEO services, courses, and even events—so it’s less an ‘AI journey’ and more a general business journey.

aibusiness fundamentalslesson