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This article presents a five-dimension AI operating model drawn from real-world enterprise deployments. Across all five dimensions (workforce augmentation, AI-assisted development, agentic computer use, autonomous workflows, and AI-assisted analytics), the author argues that the technical challenge is typically solved before the organizational one. The piece...
A clinical trial data platform is a collection of systems with different risk profiles, different regulators watching them, and different answers on whether to build or buy. Some components should be purchased from established vendors. Others are better built or customized by your own engineering team. Getting the split wrong can cost millions in wasted validation work, compl...
AI-powered Clinical Decision Support (CDS) systems are a multi-billion-dollar market growing at double digits annually, yet most of them get ignored High-profile failures at IBM Watson for Oncology, Epic’s Sepsis Model, and Optum’s risk-prediction algorithm exposed the same root causes: poor data quality, workflow misalignment, lack of explainability, and absent external vali...
Those AI coding tools are fast, and your developers love them. But somewhere in all that AI-generated code, there’s a security vulnerability that slipped through code review.
Key Points Security risks are often the result of missing context. AI-generated code can introduce injection flaws, XSS, auth gaps, and unsafe data handling. AI tools amplify supply chain ri...This article argues that AI production failures stem from specifications that capture processes without encoding organizational judgment. The author introduces the Specification Architect role and a five-layer framework (Intent, Semantics, Realization, Determinism, Execution) illustrated through a hospital AI system that ranked patients correctly by its own...