On the necessity of ontological rigor in scientific discovery 🧵

1/ In immunology, we're trained to compartmentalize: innate vs adaptive, cellular vs humoral, different pathways for different contexts.

This paradigm serves us well—until we encounter problems that transcend these boundaries.

You may have noticed I've been quieter on socials—heads down, building IP. MedAdvocate.app & more: regulatory-friendly, deep patent coverage.

1) From AI Trenches to Epistemology—(There’s a Twist Coming for Immunology) I'm pretty sure....

Been in the AI trenches—think Cursor, Claude & co. If you’ve tangled with stubborn models, you know: real alchemy is pointing code at your “happy place.”

Mine’s science. #AI #Immunology science.

Left immunology in 2009, jumped back to tech in 2023, now building AI immune models. When I left, Danger Theory wasn’t generally known—100% not known in my company. It still seems rare even in 2025. #immunology #AI

Wild to see biotech folks using “danger theory” ideas but never naming the theory. How often do fields reinvent breakthroughs with no common language? Are there other cases where big ideas spread but stay unnamed? #science #ontology

AI keeps hallucinating and medicine keeps missing tough diagnoses. What if both failures stem from unclear ontologies? I use atomic units of info—union, intersection, difference—to clarify these black boxes.

Launching MedAdvocate.app bringing actionable AI guidance to rural healthcare. Looking for visionaries in healthcare , Comp Biology, those building deeply integrated Bio/AI.

Interested in innovative collaborations -or just chat if curious: danger theory+AI, or the future of health tech! 🚀