John Saxon
About
Outside of my day job, I've been creating solutions for small businesses for over twenty years. It started with Webpark in 2003. A consulting and hosting company that grew from two eBay servers in a basement into a real operation running on dedicated hardware in a downtown datacenter. Fourteen years in, it was growing faster than I expected. With a young family at home, I chose day-job stability over the entrepreneurial leap. It was exciting to build something real, and I learned what it takes to run a business from the ground up.
I spent sixteen years at AESO, working my way from desktop support through Windows Server teams, NetApp storage administration, infrastructure design, and team leadership. Alberta's power grid is the kind of environment where mistakes aren't theoretical. That's where I learned how to build things that scale, stay secure, and don't fail.
At Benevity, I started managing the IT team, then moved into vendor management where I got exposure to hundreds of enterprise applications and learned what's out there and what it can do. During that time, I started coding with AI the day ChatGPT 3.5 dropped in late 2022. It was rough. The models hallucinated, the code barely worked, every project felt like pushing a boulder uphill. But I kept going. Once the tools got good enough (and I got good enough with them), I started building BuildBot. Two years and millions of lines of code later: nine integrated applications for small businesses, co-founded with my daughter Katie. Then I recognized how fast software delivery was changing and completely revamped BuildBot into an AI custom app delivery model. I've since built a full application factory that autonomously handles architecture setup, deployment, testing, documentation, and production readiness, end to end. What used to take teams weeks now takes under an hour.
Coming into AI development without a traditional coding background taught me something different. I learned how to harness the AI itself. How to prompt it for good results, how to prep its context with the right information, how to auto-document and update its knowledge files along the way, how to give it skills. I think about it the way Anthropic describes it: a narrow bridge with cliffs needs exact guardrails and precise instructions, but an open field with no hazards just needs a general direction and trust. Knowing which one you're on is the whole game.
I used to be the architect of the solution. Now in 2026, I'm the input to the architect and the checker at the end. My 10-80-10 rule: humans do the first 10% (finding the information, prepping good input, shaping the plan), AI does 80% of the work, and humans check the last 10% and tweak the result. The hard part over time is pushing on those two 10% ends. That's what creates full automation.
I pay attention to a lot of people on the forefront. Eventually I start seeing glimpses of where I can engage in my own way. That's not genius. It's pattern recognition from paying attention.