TERRAIN AI Framework
Frequently Asked Questions
What is the TERRAIN AI Framework?
TERRAIN is a practical, seven-phase Agile framework for delivering AI initiatives, built from real field experience adapting Agile for the ways AI projects behave differently from standard software work. It started as a book and is now maintained in the open as a free community resource.
Is TAIF really free?
Yes. The framework, the phase guides, TAIF values, and the chapters published so far are free to read on this site, with no sign-up or paywall. The complete print and Kindle edition of the book is also available on Amazon for readers who want a physical copy.
How does the website relate to the book?
The site is the living, community-shaped home for the ideas in the book "TERRAIN AI Framework: A CIO's Guide to Artificial Intelligence Transformation." Chapters are being published here progressively, and the framework itself keeps evolving based on real-world feedback in a way a printed book can't.
When will the rest of the book be available online?
All chapters are scheduled to be free to read on this site starting September 2026. Until then, a sample -- including the preface and introduction -- is already live, and the complete edition is available now on Amazon.
Who maintains TAIF?
TAIF is stewarded by Amod "Andy" Desai, the framework's original author, but it's shaped in the open by the community that puts it to work -- values, case studies, and feedback all go through review before they're published. See the About page for the full story.
How can I contribute or submit a case study?
Use the Submit a Case Study page to share how TAIF played out on a real project, success or failure both. If a phase is missing something or a value doesn't hold up in your context, use Suggest a Feature instead. Every submission is reviewed before anything goes live.
I found an error or have a question that's not answered here -- who do I contact?
Reach the TAIF team through the Contact page for press, partnerships, corrections, or anything else that doesn't fit the feedback or case-study forms.