AI systems are increasingly composed of multiple specialized agents working in concert. This architectural shift — from single monolithic models to multi-agent constellations — improves capability but introduces new governance challenges, especially in healthcare, where role clarity and safety are paramount. This paper explores the unique governance risks that emerge when AI agents collaborate in chains, identifies the failure modes that single-agent safety frameworks cannot detect, and proposes four conceptual principles that a governance substrate must embody to address them. The focus is on the why, not the how — on governance rationale, not operational mechanisms.
Narnaiezzsshaa Truong (Wed,) studied this question.