AI projects are fundamentally discovery‑driven, not requirements‑driven. Success comes from structured learning across multiple dimensions.
Discovery is not a separate activity, it is the lifecycle. But we need a new language to talk about it. The old “life cycle” implies sequential phases you complete and close. AI projects do not work that way.
We propose a new construct: Discovery Vectors.
A vector is a directed force; it has magnitude and orientation. In an AI project, multiple discovery vectors operate simultaneously, continuously, and iteratively. They are not phases; they are lenses you apply at every stage. Some vectors are anchored in specific phases; others cut across everything.
The Seven Discovery Vectors of the Managing innovative AI Projects (MIAP) Framework
Five Primary Vectors
Two Cross‑Cutting Vectors (Run Through All Phases)
Together, these seven vectors form the Discovery‑Driven AI Project Lifecycle. They are not sequential; they are simultaneous, overlapping, and recursive.
© 2026, Jayakumar K R. All rights reserved.
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