Writings
Writings on AI, data, and the organizational realities behind success and failure.
The Feedback Loop Nobody Built
Most healthcare AI governance focuses on deployment, validation, and compliance. Far less attention is paid to what happens afterward. When nobody owns the process of monitoring real-world performance, clinician adaptation becomes the only feedback loop that reliably functions.
Why the Person Holding the Map Still Matters
Models are useful precisely because they simplify reality. The mistake is expecting them not to. From clinical scores to AI systems, the real challenge is not building perfect maps, but developing the judgment to know where their edges are.
The Validation Trap
Validation exists to reduce uncertainty, not eliminate it. Yet many organizations quietly transform validation into something else entirely: a mechanism for avoiding decisions. The result is not caution. It is a different kind of risk.
Explainability Is Not About Explaining the Model
In healthcare and science, trust rarely comes from understanding every internal parameter. Explainability is less about perfect transparency than about building systems humans can safely reason with.
Agentic Coding Collapses Build Costs. So Why Is Healthcare Software Still Hard?
As agentic coding drives software creation costs toward zero, competitive advantage shifts toward workflow ownership, governance, operational trust, and the permission to operate.