Newer Is Not Truer: Three Presuppositions Behind the Recency Rule in Long-Term Agent Memory, and Why Retaining Both Records Relocates the Decision Rather Than Making It

Abstract

An agent with persistent memory writes its own records, and two of them can disagree. Across the published systems examined here the resolution runs in one direction: the newer record supersedes the older. This paper argues that the direction is not wrong so much as underdetermined, and that the published evidence for it is thinner than its uniformity suggests. Preferring the newer record presupposes three things. It presupposes a key that fixes which records are candidates to conflict at all, since two statements about a preference made in different contexts are not a contradiction. It presupposes that the recorded order of writes tracks the order in which the facts held - the distinction temporal data management draws between transaction time and valid time - and one published agent-memory system states in its own abstract that what it verifies is chronology and provenance rather than semantic supersession. And it presupposes that a newer record is at least as trustworthy as an older one, which runs against operation-level evidence that memory systems generate and accumulate errors at exactly the extraction and update stages that produce new records. The paper further argues that one word is carrying two questions that belief revision separated decades ago - the world changed, versus the earlier record was wrong - and that a rule correct for the first is wrong for the second. The turn now underway, retaining both records and labelling them, is endorsed here and then deflated: it converts a write-time decision into a read-time one, and the read-time measurements are the weakest numbers in this file. Nine studies and one reporting convention that would settle the open parts are named. No experiments are reported here.

The literature search, drafting and citation verification for this paper were carried out with AI assistance under the author's direction. Every citation was machine-verified against the arXiv API and Crossref before inclusion, and every quantitative claim was read back against the cited source's own abstract. The author is responsible for the final text and for all claims made in it.

About the author

Pranay Mahendrakar is an ai specialist and large language model engineer based in Bengaluru, India. He builds production artificial intelligence systems and publishes open-access research on how those systems fail. See all 66 papers by Pranay Mahendrakar, or his ORCID record.