Why I Built This Site

I have spent over a decade leading enterprise transformation work. The artifacts that kept getting used after project closeout were never the status reports or steering committee decks.

They were the systems.

The pattern that kept running

On nearly every project, I set up an MS Project plan and a SharePoint workspace. Over time, I started improving the system around the plan. I built structured Microsoft Lists trackers, refined workspace design, and used Power Automate to remove repetitive follow-ups.

Nobody put that in the charter. It kept running anyway.

That pattern showed up often enough that I stopped treating it as a side effect of project work and started treating it as the point.

By day: healthcare transformation delivery

I am a Business Initiatives Consultant at UnityPoint Health in the Transformation Management Office. I have led healthcare IT efforts across clinical and digital domains, including Epic integrations with medical devices, telehealth and virtual nursing initiatives, and AI-enabled monitoring workflows.

I also led a multi-year patient experience digitization program through the MyUnityPoint portal. Patients can now schedule appointments, complete pre-visit forms, sign documents, make payments, and access test results and provider notes. A parallel effort integrated online scheduling into the provider directory so new patients can search and book directly.

Healthcare IT requires constant translation between clinical needs and technical constraints. My core delivery stack is Microsoft 365 and Power Platform: SharePoint, Teams, Microsoft Lists, Power Automate, Power BI, Copilot, and Copilot Studio.

Where AI fits and where it does not

I have been building AI capability into project delivery since 2023 through PMI coursework and direct implementation work.

In practice, AI works when it is grounded in a defined workflow with clear ownership. It fails when it is layered on top of broken process and called transformation.

At work, I focus on Microsoft-first patterns that align with enterprise governance. In my homelab, I test broader tooling, including Hermes Agent, Claude, Gemini, Open WebUI, and Ollama, to pressure-test ideas before recommending them.

Building things breaks assumptions faster than reading about them.

The homelab

A few years ago, I built my first computer, and that project pulled me into self-hosting, Linux, and home infrastructure. What started as a desktop build has grown into a small lab that spans my Windows workstation, a Linux mini PC, a Raspberry Pi, and a dedicated Home Assistant box.

My Windows desktop handles local model testing and heavier AI work. I use Ollama, LM Studio, llama.cpp, and GGUF models to compare local inference options before I decide what belongs in my workflow. When I want to keep an AI task local, the desktop becomes the practical choice because the mini PC and Raspberry Pi cannot provide the same local inference performance. For those lower-power machines, cloud models still make more sense for heavier agent workflows.

My main server runs Ubuntu 24.04 on a Linux mini PC behind Cloudflare Tunnel. It hosts the services I use every day: Open WebUI with Ollama, n8n for automation, Vaultwarden for password management, Vikunja for task tracking, and Obsidian LiveSync for notes. I connect selected MCP tools into the AI layer so agents can work with live systems instead of only generating text.

The Raspberry Pi, makerpi, runs Hermes Agent, my always-on Telegram and Discord gateway for agent workflows. Home Assistant runs separately on a Dell Wyse thin client, which keeps smart home dashboards separate from the rest of the lab.

Why I publish this work

I started this site to document what I am learning through Microsoft 365 work, automation projects, and the home lab systems I build outside of work.

I have spent several years learning through Microsoft Learn, technical communities, newsletters, blogs, YouTube, Microsoft MVPs, and other industry experts. That habit shaped how I work. I learn best by building, testing, documenting, and sharing what changed along the way.

Documentation and knowledge sharing have always helped me support teams and projects. This site gives me a public place to turn that habit into something more useful: practical notes, lessons learned, implementation details, and honest writeups about what worked and what did not.

If a post helps someone learn a new concept, fix a workflow, or avoid a mistake I already made, the site has done its job. Over time, I hope this work helps me contribute more meaningfully to the Microsoft 365 community.

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