Agentic Institutions: Organisational Memory, Correction and Continuity Across Successive AI Agents

An organisation can keep every conversation with its AI assistants and still repeat a mistake it has already corrected. The problem is not simply whether information survives. It is whether later participants can recover its grounds, recognise its limits, challenge it when circumstances change, and act on it appropriately. This paper proposes Agentic Institutions as a research programme within applied and social epistemology, concerned with the arrangements through which people, models, records and tools sustain work across successive sessions. It distinguishes institutional continuity from justified learning, and the preservation of a claim from the preservation of reasons to accept it. Organisational memory, distributed cognition and research on routines supply established foundations; recent agent-memory systems provide close technical predecessors. A bounded examination of CounterProof's library and retrieval materials illustrates a specific difficulty: a correction may be recorded while an older summary retains the withdrawn claim. The observation motivates inquiry but supplies no estimate of system-wide performance. We propose a controlled study of repeated handovers, including valid corrections, mistaken objections and changing conditions. The proposed main comparison tests incremental value, at matched resources, over one comparison condition that combines retrieval, simple archive repair and generic source checking. Its implementation and final protocol remain to be specified. Outcomes include later decision quality, recurrence of corrected errors, false reversals, appropriate uncertainty and human effort. The broader aim is to investigate how institutions working with AI can accumulate useful knowledge while remaining capable of revising their own methods. Conceptual preprint; not peer reviewed. The proposed study has not been run. AI-assisted manuscript criticism and its limits are described in the accompanying review summary.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-28
DOI
https://doi.org/10.5281/zenodo.23727632
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
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preprint

Agentic Institutions: Organisational Memory, Correction and Continuity Across Successive AI Agents

Soons Luuk
7 links
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
preprint

Agentic Institutions: Organisational Memory, Correction and Continuity Across Successive AI Agents

Soons Luuk
preprint en

Abstract

An organisation can keep every conversation with its AI assistants and still repeat a mistake it has already corrected. The problem is not simply whether information survives. It is whether later participants can recover its grounds, recognise its limits, challenge it when circumstances change, and act on it appropriately. This paper proposes Agentic Institutions as a research programme within applied and social epistemology, concerned with the arrangements through which people, models, records and tools sustain work across successive sessions. It distinguishes institutional continuity from justified learning, and the preservation of a claim from the preservation of reasons to accept it. Organisational memory, distributed cognition and research on routines supply established foundations; recent agent-memory systems provide close technical predecessors. A bounded examination of CounterProof's library and retrieval materials illustrates a specific difficulty: a correction may be recorded while an older summary retains the withdrawn claim. The observation motivates inquiry but supplies no estimate of system-wide performance. We propose a controlled study of repeated handovers, including valid corrections, mistaken objections and changing conditions. The proposed main comparison tests incremental value, at matched resources, over one comparison condition that combines retrieval, simple archive repair and generic source checking. Its implementation and final protocol remain to be specified. Outcomes include later decision quality, recurrence of corrected errors, false reversals, appropriate uncertainty and human effort. The broader aim is to investigate how institutions working with AI can accumulate useful knowledge while remaining capable of revising their own methods. Conceptual preprint; not peer reviewed. The proposed study has not been run. AI-assisted manuscript criticism and its limits are described in the accompanying review summary.

Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
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Agentic Institutions: Organisational Memory, Correction and Continuity Across Successive AI Agents — Soons Luuk · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS