AI Shaping: Turning General-Purpose AI into Productive AI Work

Recurring AI-enabled work can produce useful outputs while leaving people to reconstruct source basis, domain fit, work state and resumption logic. AI shaping is the operating-model discipline that establishes shaped intelligence to carry a reusable and iteratively improvable domain work pattern and reusable work basis under human direction. Shaped intelligence carries more of the two-sided burden — domain-practice and subject-context, and work-state and resumption — so useful output can become grounded, reviewable, repeatable and resumable productive AI work. The direct-shaping approach establishes bounded shaped intelligence without first materialising separate AI-shaping intelligence; the mediated-shaping approach uses separately reusable AI-shaping intelligence to carry the shaping pattern. This paper defines the category, supports category-fit decisions and routes readers to separate Project-managing and Product-managing evidence papers. It does not establish capability performance, measured improvement or implementation-transfer authority.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-30
DOI
https://doi.org/10.5281/zenodo.21701316
Primary Topic
Software Engineering Techniques and Practices
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Shaping: Turning General-Purpose AI into Productive AI Work

Kurni Kwok
Zenodo (CERN European Organization for Nuclear Research)
Software Engineering Techniques and Practices
article

AI Shaping: Turning General-Purpose AI into Productive AI Work

Kurni Kwok
article en

Abstract

Recurring AI-enabled work can produce useful outputs while leaving people to reconstruct source basis, domain fit, work state and resumption logic. AI shaping is the operating-model discipline that establishes shaped intelligence to carry a reusable and iteratively improvable domain work pattern and reusable work basis under human direction. Shaped intelligence carries more of the two-sided burden — domain-practice and subject-context, and work-state and resumption — so useful output can become grounded, reviewable, repeatable and resumable productive AI work. The direct-shaping approach establishes bounded shaped intelligence without first materialising separate AI-shaping intelligence; the mediated-shaping approach uses separately reusable AI-shaping intelligence to carry the shaping pattern. This paper defines the category, supports category-fit decisions and routes readers to separate Project-managing and Product-managing evidence papers. It does not establish capability performance, measured improvement or implementation-transfer authority.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 3%
Software Engineering Techniques and Practices
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