How do you differentiate Maker School from other AI automation communities like Jack's?
Yeah, it's a great question. For those who don't know, I run Maker School community, and I'm currently number three on the revenue leaderboard with about $292k. My success comes from how I package the community. I position it as a B2B offer where members pay $184 a month to learn how to get their first paying customer for an AI or automation service. In 90 days they earn back the money they spent (not counting tool costs), effectively getting a customer that pays around $1,000, which feels like a five‑to‑six‑times ROI. While Jack's community and other AI automation groups were first movers just by being the go‑to place for AI talk, I took a sniper‑rifle approach: I niche down to teaching how to build a business, not just how to use AI. Now I'm integrating AI and automation curriculum directly into Maker School—I've finished a make.com and an NAN accelerator and just need to record the videos. We also still do Q&A and similar offerings. Most other automation communities stay broad and less differentiated; I solve the specific problem of wanting to sell something with AI/automation and then actually doing it.
I just added a big workshop module to Maker School — just in the final QA touches here. Essentially this is an in-depth step-by-step guide to selling education, selling structured education to companies, selling training to companies, and so on. So I have actually added that in, and that is more AI adoption, engagement, enablement type stuff. Aside from that, I've also shifted towards teaching people how to build their own brands within the confines of Maker School, doing so in highly effective ways and then combining that with outreach and so on to really get the 80/20. So yeah, Maker School's evolved quite a bit — and thank God I called it Maker School and not Gemini 3.1 Pro school, huh? That's where I'm at with that.
I started with Harvard CS50, then taught myself computer science from the ground up, excluding languages and compilers, distributed systems, and operating systems. I completed nanotech to Tetris, building a computer from scratch. After that, I learned AI from scratch via a course that just listed introductory material, then I began training models—first a TensorFlow model called Stalan 2 that generated faces, then Gwarn's 'This Wu Does Not Exist' which I turned into an anime face generator, which I found hilarious and turned into a business called One Second Painting. I scaled that to about $3,500 per month by selling AI-generated art, but Midjourney's release destroyed that business. I had been selling NFTs, which gave me hands‑on AI experience. I then used that experience to freelance write while aiming for $10k/month, employing GPT‑3 for content. I also spent six months to a year locked in my room learning make.com and Zapier, building automations for my One Second Painting business and later for a second venture with a business partner. Eventually the money came from disproportionate time invested, leading to a compressed business model: get your first customer quickly, then worry about everything later. I realized most of the low‑level AI skills I learned aren’t used today, but the practical experience with automation platforms like make.com and Zapier, plus building info products, allowed me to scale to $100k/month through a blend of an AI automation agency and information products.
I'll be honest: AI auditing and infrastructure is just a repackaging of what we already do—same service, different packaging to look and sound new. It's a smart move for content creators because audiences get fatigued with the same offering over time, but there's no real fundamental difference in the deliverable; only the packaging changes slightly. There's no special support needed to make that transition; we continue with the same business model under the hood and may rebrand later when the market tires of the 'AI automation' keyword.
First, I’d join a community like Maker School—not just to use my own products but because membership gives you deep discounts (often a 10x return) on AI platform credits and payment‑processing fees. With those savings I’d start by learning a visual drag‑and‑drop automation builder (such as the n platform) for about four to six hours; that teaches you the fundamentals of systems, workflows, JSON, HTTP requests, etc., which accelerates everything else. Next I’d spend another four hours on a Claude‑code course that covers the technical setup, agent communication, model selection, and so on—roughly ten hours total. After that foundation, I’d devote virtually all remaining time to acquiring customers; the first 90 days would be less than 1% spent on learning and the rest on outreach. You need a customer to actually enter the arena, so I’d use Maker School’s day‑by‑day accountability to hit call and outreach targets, then loop back to upsell from any lower tier to higher ones as the relationship grows.