AGIF Tasklet Cells: Verifier-Backed Offline AI Artifacts for Native Applications

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Authors: Danish Ali Khan
Cited by: 0

Abstract

Whitepaper for “AGIF Tasklet Cells: Verifier-Backed Offline AI Artifacts for Native Applications.” This record contains the paper PDF for the AGIF Tasklet Cells artifact model and its bounded empirical evaluation anchored to the clean N30 evidence baseline at commit 78a1635 (2026-03-09). The paper presents Tasklet Cells as bounded, contract-driven offline AI artifacts for native applications, executed under local verification and fail-closed enforcement. The evaluation is scoped to the released evidence bundle and should be read as evidence for the described artifact model and case-study boundaries, not as a claim of general intelligence. Public software repository:https://github.com/Ahsadin/agif-tasklet-cell-public Public evidence release supporting this paper:https://github.com/Ahsadin/agif-tasklet-cell-public/releases/tag/paper-evidence-r1-78a1635-clean

Fields of Study & Subjects

Logic programming and type systems Security and Verification in Computing Safety Systems Engineering in Autonomy

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 March 2026
Language
EN
Document type
Preprint