I learned operations before I learned software. That turned out to matter.
My early career was in hands-on, measurable industries. Various blue-collar trades where performance is counted and systems either work or they don't. There's no "we'll iterate next sprint" when a vehicle is on the lift.
What those environments gave me wasn't a trade. It was a way of thinking. You map the problem before touching any tool. You identify the failure points first. You build toward a defined outcome, not the excitement of the build.
The numbers backed it up. In automotive during peak season, I cleared 17 cars a day. Approximately 318% over typical technician output. That didn't come from effort alone. It came from removing every step in the process that didn't need to exist.
That's the same logic I apply to every AI system I build at Daubix. Strip out what's unnecessary. Automate what's repeatable. Build only what should be built.