Principal AI Solutions Architect with twenty years of software systems design. I build enterprise AI systems at a Fortune 500 company and consult independently on AI architecture, vendor evaluation, and technical training.
I have worked as a software architect and engineer for over twenty years, across logistics, healthcare, ecommerce, financial services, and insurance. The work has included graph-based routing engines, real-time prediction systems, healthcare rules engines, and ecommerce platforms.
I began working with LLMs approximately two years ago — as a systems architect evaluating where the technology fits inside production software, not as a researcher or data scientist. My initial position was skeptical, informed by prior technology cycles in which capability was consistently overstated relative to production reality.
The assessment I arrived at is narrower than the common framing on either side. LLMs are effective in specific, well-defined problem spaces and unreliable in ways that vendors tend not to disclose and buyers tend not to know to ask about. In most implementations, the determining factor is not the model. It is the architecture around it — integration design, evaluation methodology, and how the system handles the cases where the model is wrong.
I am currently a Principal AI Solutions Architect at a Fortune 500 company, designing and building AI systems for enterprise use. Through my independent practice I provide assessment, architecture, proof-of-concept development, and technical training: evaluating AI decisions before the budget is committed, and helping technical teams build systems that hold up in production after it is.
I do not sell AI as a general-purpose solution. Where it is the wrong tool for a given problem, I say so, and I document why.