About me

Over the last several decades, I’ve built scalable systems for automation and infrastructure, enforcing policy and architecting platforms designed for control, repeatability, and resilience.

Today, the paradigm is shifting.

With artificial intelligence, automation evolves beyond static logic. It becomes predictive, adaptive, and increasingly reflective of the dynamic patterns found in nature, a concept known as biomimicry.

No longer limited to scripts and interval-based information gathering, intelligence can now take form in the physical world through embedded models, sensory feedback, and real-time decision-making. This work includes building machine learning transformation pipelines, training embedded models for vision, text, and multimodal inputs, and deploying inference to edge devices. The goal is to develop systems that learn, react, and adapt at the pace of life.

The future of automation is not just digital. It’s sentient.

These are systems that tend to daily rhythms with the same diversity and nuance found in nature, augmenting capability, enhancing physical environments, and abstracting away the friction of everyday repetition. This site documents that work.