I help make complicated technology work.

Most of my background is in enterprise IT: infrastructure, storage, virtualization, data protection, systems, security, recovery, and the automation around them.

But my job has rarely stopped at the technology.

I’ve led teams, run a hospital IT department, owned a managed-services business, worked in large energy and financial-services environments, managed vendors and budgets, and been responsible for systems other people depended on.

Today I spend a lot of my time taking work people are doing manually and figuring out how to make it repeatable, controlled, and easier for someone else to run.

Sometimes I’m building the solution.

Sometimes I’m working through the architecture.

Sometimes I’m helping people figure out what they really need before anybody builds anything.

I can get down into the code and infrastructure, but I can also explain the same problem to the person responsible for the business decision.

That combination is probably the best answer to what I do.

I can start solving a problem without first spending six months learning every tool involved.

AI helps me research the unfamiliar parts, understand documentation, write code, troubleshoot, compare options, and test what we’ve built.

I’ve used it for enterprise infrastructure automation, operational reporting, web applications, apps that helped run a 200-person encampment, cemetery records volunteers can reach from a phone, and even an iOS application.

That doesn’t mean I suddenly know everything.

I still have to recognize when we’re making something too complicated, when a permission doesn’t work the way we thought, when a test is checking the wrong thing, or when something says it worked but didn’t actually accomplish the job.

AI can help me figure out how a tool works.

I still have to figure out whether we’re doing something sensible with it.

Sometimes the interesting part of a job is what it changes about the way I think afterward.

A test rejects good work. A successful request hides an email that never arrived. A manual process turns into something much more useful once I stop thinking about it as just a manual process.

Field Notes are where I work through those things and what I think I learned from them.