NOW ON UDEMY
A practical, field-tested framework for EA practitioners who want their work to drive real decisions — not get filed and forgotten.
Udemy · Now Live
Fit-for-Purpose Enterprise Architecture — Practitioner’s Course
10 modules · 56 lessons · ~4.15 hours
Stop producing architecture that gets ignored.
Opens on Udemy
Fit-for-Purpose Enterprise Architecture and The Architect’s Blueprint — both available now on Amazon for Paperback and Kindle version.

This book introduces the Fit-for-Purpose concept: a practitioner framework, developed through more than two decades of field engagement, for configuring every architectural effort to the specific context in which it is being applied. The Fit-for-Purpose concept is independent of any particular EA framework; it can in principle be applied to any structured approach to Enterprise Architecture.

This is my debut book in The Enterprise Architecture World Series. This is a novel about organizations as built things — with load-bearing walls, structural dependencies, and the persistent gap between a capability that is present and a capability that is structurally deployed. It asks the question that sits beneath every engagement, regardless of methodology: Do the people building this believe it is worth building?
A full-semester course for CEDT students, structured around the Fit-for-Purpose concept as the organizing lens for every Enterprise Architecture engagement and delivery. Rather than teaching frameworks as fixed prescriptions, the course trains students to configure architectural thinking to context — drawing on more than two decades of field engagement across industries and geographies.






Invited to deliver sessions for the Business Intelligence Systems course at Chulalongkorn Business School. The sessions covered BI applications, focusing on how organizations translate data into operational decisions through the CRISP-DM framework, common reasons why BI initiatives fail, and the distinction between AI-enabled insights and data-driven analytics. Topics included Predictive Analytics, applied Machine Learning, and AI, with an emphasis on how ML techniques are selected, scoped, and executed within real-world engagement contexts.