arXiv — cs.AI preprintsInternational15 October 2026
WorkBorne: Discovering Agentic Tasks from Real-World Artifact Transitions
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arXiv:2610.14915v1 Announce Type: new Abstract: Developing terminal-based agents for long-horizon execution demands synthetic tasks that tightly couple complex instructions with authentic, interactive environments. However, current automated synthesis suffers from a fundamental asymmetry: instruction-oriented methods fabricate low-fidelity, synthetic environments, whereas resource-oriented methods treat real artifacts merely as static inputs, degrading task instructions into shallow, trivial operations. To address this limitation, we introduce WorkBorne, a synthesis framework that uses artifac
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