From AI pilot to validated capability
A practical operating model for moving high-value use cases through risk review, evaluation, and controlled release.
8 min readINSIGHTS
Ideas for building AI that holds up.
Practical thinking on governed AI, enterprise agents, data products, evaluation, and the operating changes that turn capability into value.
The case for bounded agents in life sciences
Why the most useful enterprise agents are explicit about scope, evidence, and the moments that require a human.
6 min readDesigning an AI evaluation system
A layered scorecard for quality, safety, grounding, workflow performance, and business outcomes.
10 min readWhat should an AI council actually decide?
A decision architecture for moving beyond broad principles toward timely, consistent action.
5 min readRAG is a data product, not a prompt pattern
Why provenance, meaning, permissions, curation, and feedback determine the quality of enterprise retrieval.
7 min readA pre-production checklist for AI agents
Twelve questions covering scope, tools, identity, evidence, exceptions, human review, monitoring, and recovery.
9 min readA NOTE ON OUR LIBRARY
Useful, not exhaustive.
Our insights library is being built around questions we repeatedly encounter in real programs. We publish when we have something specific, tested, and useful to add—not to keep a content calendar full.
Have a question worth thinking through together?
Bring us the consequential problem—the one that crosses data, technology, regulation, and human judgment.
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