Short, field-tested essays on enterprise transformation, AI adoption, and the architectural decisions that compound over time. We publish when we have something worth saying.
A practical framework for assessing AI readiness across data, workflow, risk, and culture - before committing budget.
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Quality attribute scenarios, reversible decisions, and the architectural habits that keep optionality cheap.
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Why most "strangler" programs fail at the boring parts - and how to plan for them.
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How to hold the line on customization without creating friction with the business - and when to let it flex.
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Migration patterns that protect the business while keeping your program honest about quality.
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Why AI governance belongs in the architecture and operating model - not in a policy document nobody reads.
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