As internet-scale software began reshaping the world in the 1990s, I faced a consequential professional choice — one that would influence not only my career but also my family and our long-term stability.

I had completed an advanced degree in electrical engineering on a computer science foundation, while working inside a process-focused engineering organization. I was moving into roles of increasing responsibility just as the internet transformed how software would dominate every industry. I had to decide to pursue executive management, or to adapt -- to preserve and extend my technical edge.

I had advanced to a senior leadership role in an RF products company, and when we sold that company, I abandoned work on an MBA. I switched my continued training to extend my Computer Science roots and Electrical Engineering linear systems background.  I moved to consulting roles, accepting work either leading or contributing to large information systems programs.

Consulting engagements presented varied challenges on the cutting edge of information retrieval, cloud-based data warehouse systems, and graph analytics. The pandemic allowed me to focus on machine learning, and that led to engagements featuring embedding-based classifiers and workflow systems — as well as infrastructure advancements such as containerization, and kubernetes.

These choices shaped the trajectory of my career, and delivered me a unique combination of experience, technical skills, independence and adaptability. Today, I work defined engagements in areas the align with my own interests in emerging Agentic AI platforms, and process maturity modeling.

I thrive in the role of vision holder and communicator.

Today I work with PE-backed defense and industrial technology companies in defined, time-bounded engagements — bringing pattern recognition from four decades of production systems to organizations where the team is in place but their confidence doesn't match the apparent risk