At 13, I tried to build a payroll system. The tools just weren’t there yet.
In 1982 I got my first computer. It had 3.5KB of RAM. I immediately went out and bought a 16KB expansion pack. Most kids my age were playing games on theirs. I started building a payroll system for my father’s sheep shearing business.
I never finished it. Not because I couldn’t figure out the logic - I could. But the computer stored everything on a cassette tape. The kind you recorded music on. Sequential access only. No way to jump to a record, update it, jump back. For a payroll system, that’s a fundamental problem. The tools weren’t there yet.
I was 13. I subscribed to computer magazines. I taught myself two programming languages. I took every computer class my school offered. The ambition kept outrunning the available tools.
That pattern has never really stopped.
Mathematics degree. Actuarial career. And a shift into marketing.
I went through university studying mathematics - back when you booked time in the computer lab because nobody owned a laptop. I remember walking across campus one day and a friend mentioned he’d just been using something called the internet to research something. I asked him what that was. He explained it. This is how far back we’re talking.
After university I landed in an actuarial role. Highly mathematical, highly technical, considered one of the harder career paths you can take. I wasn’t finding it challenging enough. Someone in leadership suggested I’d be better suited to marketing. For the first time I was exposed to a completely different world - persuasion, psychographics, demographics, the mechanics of why people actually buy things.
That began a pattern that has defined my entire career: flipping between the technical world and the marketing world, never quite fitting neatly in either, always carrying both.
Government databases. 150 million records. SAS pushed to its limits.
I spent years in government database work after that. Hundreds of millions of records. SAS software pushed to capabilities most users never touched. Same instinct, new tools - find what the system can do that nobody else is doing yet, and do it.
$100,000 a month on Amazon - and my business decisions were driven by automation.
Then in 2009 I pointed everything at online business.
First was a website about gout. Built it, got it to $1,500 a month, watched Google change the rules and wipe it out overnight. Then Amazon. Four products, eventually $100,000 a month in US dollar sales. But here’s the part that doesn’t make it into most Amazon success stories: I wasn’t just selling. I was building systems behind the business.
Running serious inventory on Amazon means tracking sales, stock at the warehouse, stock already at Amazon, product on the water, product still being built at the factory. Five moving parts, all the time. Most sellers built spreadsheets and manually updated them. I wrote code that pulled it all together automatically and reported to me daily. Same with advertising - Amazon generates enormous amounts of advertising data. Too much to read by hand. I mined it the way I’d mined government databases, pulling out only the signals that actually mattered.
The principle I’d been running on since 1982 had a name by now: if I find myself doing something more than once, I’m going to automate it.
Investors bought the business. The systems were a big part of what they were buying.
The business got noticed by investors. They bought it. The systems were a big part of what made it worth buying.
Then ClickBank. Affiliate marketing, weight loss supplements. Three months where everything went ballistic - over a million dollars in sales. More volume than profit, and gone nearly as fast as it came.
I discovered no-code tools, and never looked back.
When the no-code tools arrived - n8n, Make, Zapier - something clicked into place. I built a content machine that took a blog post and automatically converted it into video, reformatted it for every platform, ran paid ads against it, and published daily without anyone touching it. I’ve been trying to build this my entire career. The tools finally caught up with the idea.
I told a room full of business owners every answer was “yes.” It was.
Not long after that I was presenting to a room full of business owners. I walked them through an automated content system I’d built - the whole thing laid out in front of them. I told them we’d answer all their questions, but I made one prediction first: if their question started with “Can we connect this to this?” or “Can I do this with that?” - the answer was going to be yes.
The first few questions came in carefully. “Can we connect this to our CRM?” Yes. “Can we automate this part here?” Yes. By the end of the session, as soon as someone started with “Can we-” the room would laugh before I even answered. Because they already knew.
That’s not a party trick. It’s a genuine belief. If it’s digital and it matters to your business, you can almost certainly automate it, connect it, or make it run without you. The question is never really “can we” - it’s “where do we start.”
I’ve been teaching Taekwon-Do for 30 years. Here’s why that’s relevant.
I’ve also been doing Taekwon-Do since 1989, and teaching since 1995. Started because a black belt stole my girlfriend and I figured I should learn what that was about. Someone told me early on I’d never stick with it. I’m a 6th Dan now. 36 years. Hundreds of students. Dozens of black belts produced.
Teaching Taekwon-Do for 30 years taught me something the AI space badly needs. When you’re a 6th Dan explaining a movement to a white belt, you don’t explain it as a 6th Dan. You meet them where they are. You break it down to what they can use right now. You give them the next step, not the whole staircase.
40 years of building systems. Now everyone wants to talk about AI.
I’ve been connecting marketing and technical thinking my entire working life, in a time when most people had to choose one. I built systems to run businesses before the tools existed to make it easy. I’ve spent 30 years teaching complex things to people who are just starting out.
In 2026 people ask me what AI actually means for their business.
If I find myself explaining the same thing more than once, I’m going to build something that explains it automatically.
Some things don’t change.