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Conceptual framework demonstrates the primacy of persistent context and bi-temporal ledgers in autonomous AI agent systems, suggesting that accumulated memory outweighs raw foundation model compute.
The Accumulating-Context Agent. The unit of value in agent systems is not the model call — it is the accumulated context: an identity that has read its own ledgers for months can draw on decisions and corrections a fresh prompt would have to reconstruct from scratch. Engines rent intelligence; the accumulation is owned. This is why identity lives on disk, why memory is bi-temporal, why ledgers must not lie, and why context-hygiene is treated as an engineering discipline with brakes, anchors, and pickup chains. Part of a series; it cites the companion campaign paper (Melikoğlu, Altınbaş & Tanrıöver, 2026; concept DOI 10.5281/zenodo.22086013). Bilingual: the full text is included in both English and Turkish. AI-transparency note: the draft was written by an AI agent under human direction (the human authors held go/no-go authority), blind cross-family jury-reviewed (producing model family excluded from the bench), and reviewed against the source ledgers by the human authors before publication.
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Melikoğlu et al. (2026) studied this question.
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