Articles.
Notes on deploying governed AI in healthcare and life sciences: architecture, regulation, and what it takes to get from prototype to production.
- Aug 11, 2026
California Proposition 44 and the Hidden Threat to Safety Net Clinics
California's November 2026 ballot carries a measure that has received surprisingly little attention outside of health policy circles, but should be keeping FQHC executives up at night. Proposition 44 — formally titled…
- Jul 26, 2026
The New Operating System for Healthcare AI
Healthcare and life sciences companies are entering a new phase of AI adoption. The first phase was about experimentation: testing LLMs, building copilots, exploring retrieval systems, validating early use cases.
- Jul 26, 2026
The Production AI Stack for Healthcare
Artificial intelligence is advancing rapidly across healthcare and life sciences. Large language models, foundation models, and new machine learning techniques are unlocking new possibilities for research, diagnostics, and…
- Jul 26, 2026
Why LLMs Alone Are Not a Healthcare AI Architecture
Large language models have dramatically accelerated interest in artificial intelligence across healthcare and life sciences. Their ability to interpret natural language, summarize complex information, and generate insights…
Why Most Healthcare AI Projects Fail
Healthcare organizations are investing heavily in artificial intelligence, yet a large percentage of AI initiatives fail to reach production. The common narrative is that models are not mature enough, or that the technology…
The AI Infrastructure Gap in Life Sciences
Life sciences organizations have some of the most data-rich environments in the world. Genomic sequencing, clinical trials, molecular simulations, and real-world evidence datasets generate enormous volumes of information.
Hallucination Risk in Clinical AI Systems
Large language models have introduced powerful new capabilities for interacting with complex datasets. However, they also introduce a critical challenge: hallucination.
How to Deploy AI in Regulated Environments (Engineering Considerations)
Deploying AI systems in regulated industries requires a different approach than deploying AI in consumer or enterprise software environments. Healthcare and life sciences organizations must design systems that satisfy strict…
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