I didn't start with tutorials. I started with problems.

I came to engineering by operating businesses and repeatedly hitting the same problem: critical workflows held together by spreadsheets, disconnected tools, and people remembering what had to happen next. Real estate, collections, trading. Eventually I stopped waiting for better software and started building it.

The path ran through systems work first: Salesforce pipelines, CRM automations, reporting dashboards. When configuring stopped being enough, I built ResolveOS, the workspace my collections job runs on every working day, and then the Velocity platform: payments, payouts, live market data, and the admin operation behind a real fintech launch.

That operating background means I write code with the domain already loaded. I know what a payment webhook has to survive because I've watched revenue depend on one, and I know which numbers an operator actually reads on a dashboard because I was the operator.

Today I practice AI-assisted software development with the same discipline I apply to everything else in engineering. I structure the repository context, define constraints and acceptance criteria before implementation, review every diff, and verify the result in the running application. Coding agents make me faster; the architecture, judgment, and responsibility for production stay mine.

The direction from here is deliberate. My titles have been founder, account manager, CRM systems developer, and product engineer, but the job underneath them barely changed: find the real problem, turn the workflow into requirements, design the system, build it, deploy it, and improve it against what production teaches. I'm now bringing that ownership into a software engineering team, with full-stack systems and applied AI as my strongest areas of focus.

I'm also formalizing the foundations at Western Governors University, where I've been enrolled in the B.S. and M.S. Computer Science pathway since January 2026.