Measurement-Before-Prediction Architecture: framework reference brief
Year: 2026
Type: article
Abstract: Most infrastructure AI deployments fail because the measurement framework was not designed before the data was collected. This framework reverses that sequence, working backwards from the prediction to the data schema. A five-step sequence for designing the measurement schema before data collection begins, so AI predictions don't require months of recalibration after go-live. What this brief contains. The framework's reference diagram, the method and its application rule, and the citation record (version, first-published and last-revised dates). It is the printable form of the framework page at https://terencekok.com/frameworks/measurement/, which remains the maintained version. Provenance and status. First published on terencekok.com on 5 June 2026; this brief is version 1.1, revised 12 September 2026. A practitioner framework, not a peer-reviewed publication. Licensed CC BY-NC 4.0.
Author: Kok, Terence
Institution: Golden Gate University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7212390239
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