Why a MedTech Exec Built a Linguistics Lab.

The Origin of the Standard

During my tenure leading communications for multi-billion dollar portfolios in MedTech and Pharma, I observed a critical failure in how the industry approached trust. We were treating "Trust" as a sentiment—something to be earned through storytelling.

But as AI began to mediate our reality, I realized that Trust is actually a geometric property.

To an AI, "Trust" is a vector alignment. To a human brain, "Trust" is metabolic fluency. The realization that these two systems—the silicon and the biological—operate on the same physics was the genesis of Linguistic Engineering.

I built this platform to document the operating model required to govern this new reality. It is designed for CCOs who understand that in the Age of AI, we are no longer just broadcasters; we are architects of the semantic supply chain.

Why Me?

For 20 years, I've led communications for multi-billion dollar portfolios in MedTech and Pharma—industries where a single misinterpreted claim can trigger regulatory action, stock volatility, or patient harm.

I've managed product launches, M&A narratives, crisis response, and investor relations in environments where precision is not optional. When AI began mediating these high-stakes conversations, I recognized that our traditional "storytelling" approach was insufficient.

This framework emerged from that necessity: a systematic approach to governing meaning when AI intermediaries stand between your message and your stakeholders. It's built for leaders who understand that in regulated industries, trust is infrastructure, not sentiment.