ABOUT
Building Architecture Through Practice
I’ve spent more than three decades working in enterprise technology, much of it around healthcare IT, enterprise imaging, infrastructure, networking, and mission-critical systems.
That experience shaped how I approach technology today: understand the purpose, boundaries, assumptions, failure modes, and how the system will be operated after the original engineer has moved on.
How I Work
Good architecture is more than a diagram, and good engineering is more than getting something to deploy. I begin with requirements, examine alternatives and tradeoffs, keep implementation aligned with design, and validate that the result behaves as intended.
Design. Build. Validate. Publish.
Documentation is part of that engineering system—not an afterthought. Requirements, architecture decisions, diagrams, standards, validation evidence, and lessons learned should help both people and machines understand the system.
Cloud Architect Lab
I created Cloud Architect Lab to develop and demonstrate this approach through practical engineering work. Each case study builds on the ones before it, moving from AWS networking and reusable Terraform patterns into applied AI, governed knowledge, semantic retrieval, evaluation, and architecture automation.
Infrastructure as Code. Architecture as Code. Knowledge as Code.
When infrastructure, requirements, standards, architecture, and engineering decisions become structured artifacts, they can serve as inputs to automation and AI—not simply documentation beside the system.
What I’m Developing
My current focus is the intersection of cloud architecture and applied AI: AWS, Terraform and automation, generative AI, Retrieval-Augmented Generation, AI evaluation, security and governance, and agent-assisted engineering workflows.
I’m particularly interested in how AI systems can reason from authoritative information, evaluate technical artifacts against engineering intent, and participate safely in real engineering work. Those are architecture problems as much as AI problems.
The Kind of Architect I Want to Be
I don’t expect an architect to know everything. I do expect an architect to investigate what they don’t know, ask useful questions, identify assumptions, evaluate alternatives, communicate tradeoffs, and make decisions that can be explained and defended.
Technical depth matters. I want to stay close enough to implementation to build prototypes, read the Terraform, inspect the network path, test retrieval results, challenge an AI response, and determine whether a system actually matches its architecture.
The best solution is not necessarily the most sophisticated one. It is the one that solves the right problem at an appropriate level of complexity, with tradeoffs that are understood.
Why I Publish the Work
Cloud Architect Lab is deliberately public. The finished architecture matters, but so do the requirements, decisions, validation, mistakes, and lessons that produced it.
My goal is to build a growing body of work that demonstrates increasing capability, sound judgment, curiosity, and a disciplined approach to solving complex technical problems.