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Foundational theory defines shared context for AI-generated software, indicating its necessity and implementation through STACY Sync.
This paper presents The Synchrony Layer as shared-context infrastructure for AI-generated software. As AI enables anyone to generate apps, workflows, agents, and automations, software ecosystems risk fragmenting across schemas, APIs, permissions, dependencies, provenance, runtime behavior, and approval rules. The Synchrony Layer addresses this by turning generated code into Generated Software Objects with formal specs, schemas, permissions, validation rules, compatibility semantics, provenance records, update policies, runtime metadata, and execution receipts. The paper serves as the foundational theory paper in a broader research arc. It defines the Synchrony Problem, explains why AI-generated software needs shared context, and positions STACY Sync as a reference implementation while leaving the full StacyOS operating-system architecture for the next paper. Blockchain and DA layers such as Avail, Celestia, and EigenDA/EigenLayer are framed as optional substrates for public shared context when synchrony must operate across independent actors. Core thesis:AI makes software abundant. Synchrony makes abundance usable.
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ARPAN MONDAL (2026) studied this question.
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