What We Taught a College Class About AI for Small Business

Quick Summary

We were recently invited to guest lecture at Dominican University's Brennan School of Business for a class and one professor in Parmer Hall. The topic: how a two-person coffee company actually uses AI for small business operations — not in theory, but in practice, with real systems running a real company.

We expected to spend an hour showing our systems. What we didn't expect was how much the conversation afterward would reveal about where people really are with AI right now, what they're confused about, and what nobody's teaching them.

Key Takeaways:

We're Jen and Eli Coleman, co-founders of Gigawatt Coffee Roasters in Bensenville, IL. We air roast coffee using a fluid bed roasting method that only a small fraction of roasters worldwide use. We attend over 250 farmers markets and events per year, sell nationwide online, and have earned over 2,600 five-star reviews since launching in February 2020.

None of that has anything to do with AI on the surface. But over the past year, we've built AI systems that handle everything from customer service to sales tax filing to SEO content creation. And that's what Professor Mike Kiyosaki wanted his students to see. Not a tech company's demo. A real small business, with a real product, using real tools to solve real problems.

Mike teaches AI Tools for Small Business at Dominican University, and he's focused on helping students understand how these tools work in the real world. So we showed up with a slide deck, a cooler full of our canned cold brew, and three live demos. But the best part of the session wasn't what we showed them. It was what they asked us.

Before we got into any demos, we asked a simple question: how many of you pay for AI? A couple of hands went up. According to widely shared data from entrepreneur Damian Player, the vast majority of the world's population has never touched AI at all. The people who have actually built something with it represent a fraction of a fraction of a percent.

That insight alone changed one student's approach during the session. He'd been running everything in a single chat for months and didn't understand why the quality of his outputs kept degrading over time. After we explained how context windows work, he said he was going to start building projects that same day.

The most interesting part of the session was after the formal presentation, when students started asking questions about their own business ideas. Not one of them asked "what's the best AI tool?" They asked about their actual problems.

One student is expanding her family's existing food business into a food truck. Her challenge wasn't AI. It was data. She doesn't have a digital point-of-sale system yet. She's working with paper receipts. How does she analyze sales patterns to figure out which locations and days perform best before she invests in a truck?

We walked her through a practical starting point: photograph the receipts, organize them by date, upload them into an AI platform, and ask it to identify patterns. What days are busiest? Which items sell the most? What's the average ticket size? You don't need a fancy analytics dashboard to start. You need your existing data in a format AI can read. From there, it can build the charts and breakdowns for you.

Another student wants to build a product business around a floatable, waterproof phone case. He's lost his phone in a lake twice and figured if the product doesn't exist the way he wants it, he should make it. What we loved about his pitch was the personal hook. He didn't start with market research. He started with a real problem he experienced. That's a story people remember, and it's exactly the kind of thing that drives early traction for a product business.

Every question from the students came back to the same thing: I have a business problem, and I need a system to solve it. AI is the tool, but the thinking comes first.

This one surprised us. When we mentioned SOPs during the presentation, most of the class didn't know what the term meant. Standard Operating Procedures. The documents that describe exactly how a process works, step by step, so that anyone can follow them.

This matters more than most people realize, and not just for operational efficiency. We've built SOPs for onboarding new employees, processing workers' compensation claims, tracking donations, filing payroll, and dozens of other processes. The last time we hired someone, we documented every single step with screenshots. We uploaded those images into AI, and it generated a clean, detailed SOP that anyone could follow to onboard a new team member for our company.

Here is the bigger picture: a smart person once asked us about our exit strategy. And the truth is, if you want to build a business that could one day run without you, or that someone else could buy, your processes have to be turnkey. Those SOPs are the foundation. Without them, the business lives in your head, and it stops working when you step away.

And here is the part that connects to AI: you can't automate what you haven't documented. Every system we've built started as a manual process we wrote down first. Our sales tax automation started as a spreadsheet Jen filled out by hand for years. Our customer service system started as replies she typed one at a time. Our blog writing system started as a manual process, post by post, before we encoded it into an AI skill.  Documentation first. Automation second. Always.

Toward the end of Q&A, a student asked something that caught both of us off guard: "You said you invested in an AI education program. But can't AI just teach you everything about AI?"

It's a fair question. And on the surface, the answer seems obvious. Of course AI can explain itself. You can ask any large language model to teach you prompting, explain how context windows work, walk you through building a project. It will do it, and it will do it well.

But here's what it can't do: show you what other people are building.

The biggest leaps we've made didn't come from asking AI to teach us. They came from seeing how someone in functional health was using the same tool to systemize client intake. Or how a real estate investor was using it to analyze deals. Or how a business coach was building an entire onboarding sequence. Those were applications we never would have thought of, because we were thinking inside our own business. The outside perspective is what breaks the ceiling.

So yes, invest in learning. Whether that's a formal program, a community of practice, a cohort, or just finding three other people who are building with AI and meeting once a week to share what's working. The tool is important. The people around you using the tool are what make you dangerous.

We walked out of Dominican University that afternoon feeling energized. Not because we nailed every slide or had all the answers. But because a small class of students and a professor reminded us why we do this in the first place.

Coffee is our product. AI is our tool. But the thing that actually drives the business forward is the willingness to show up, share what we've learned, and keep building. If you're a student, a business owner, or just someone trying to figure out where AI fits into your work, we're always happy to talk. Reach out anytime.

Stay Caffeinated! — Jen & Eli, Gigawatt Coffee Roasters