TRACE Framework: framework reference brief

A pre-deployment evaluation framework for whether a task is structurally appropriate for AI agent delegation, before architecture decisions are made. Traceability, Reversibility, Acceptance criteria, Compliance mapping, Escalation pathway. Five pre-deployment checks for whether a task is structurally appropriate to hand to an AI agent, before architecture or vendor decisions are made. 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/trace/, which remains the maintained version. Provenance and status. First published on terencekok.com on 17 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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-12
DOI
https://doi.org/10.5281/zenodo.22722217
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
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article

TRACE Framework: framework reference brief

Terence Kok
Zenodo (CERN European Organization for Nuclear Research)
Explainable Artificial Intelligence (XAI)
article

TRACE Framework: framework reference brief

Terence Kok
article en

Abstract

A pre-deployment evaluation framework for whether a task is structurally appropriate for AI agent delegation, before architecture decisions are made. Traceability, Reversibility, Acceptance criteria, Compliance mapping, Escalation pathway. Five pre-deployment checks for whether a task is structurally appropriate to hand to an AI agent, before architecture or vendor decisions are made. 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/trace/, which remains the maintained version. Provenance and status. First published on terencekok.com on 17 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.

Zenodo (CERN European Organization for Nuclear Research)
Golden Gate University (US)
Openalex Percentile: Top 8%
Explainable Artificial Intelligence (XAI)
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