AI Adoption Is a Change Project, Not Just a Software Purchase
Why AI initiatives need a defined problem, human ownership, safe experimentation, training, and evidence of value—not merely licenses and a launch announcement.
Read field noteField Notes / Working positions
Ideas become stronger when they are examined in public.
Personal writing about AI, technology, service delivery, and the leadership choices that connect possibility with practical human value.
The opening collection
Three questions worth slowing down for.
Each note begins with a position, tests it against credible evidence, acknowledges the competing concern, and ends with a practical decision frame.
Doing More with Less Requires Real Trade-Offs
A practical way to discuss constrained resources without defaulting to slogans, hidden service reductions, or technology-first answers.
Read field noteData Centers: Necessary Infrastructure with Legitimate Local Costs
A balanced case for continued computing investment, transparent local impact, and measurable standards for responsible growth.
Read field noteRecurring lines of inquiry
A point of view with room to learn.
Technology with human value
Judge new tools by the experience and outcomes they improve—not by novelty alone.
Responsible AI adoption
Connect experimentation with governance, learning, human oversight, and measurable value.
Better service systems
Make capacity, constraints, burden, trade-offs, and the full service journey visible.
Learning in public
Share working positions, sources, uncertainties, and lessons that may change with evidence.
Editorial protocol / FN-STD
Evidence before certainty.
- 01 State the position clearly.
- 02 Link the evidence behind factual claims.
- 03 Represent reasonable disagreement fairly.
- 04 Distinguish facts, inference, and opinion.
- 05 End with a useful question or decision frame.