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Relational Cognitive Telemetry for Long-Lived LLM Agent Societies: From Internal State Monitoring to Collective Performance

Chen, Ho Yiing · 2026-05-15 · Zenodo

doi:10.5281/zenodo.20234606 · PDF

Abstract

Long-lived large language model (LLM) agent systems — collectives of named agents with persistent memory, individual parameter state, and continuous interaction with each other and the world — are now technically feasible and increasingly deployed. The debugging and governance practices inherited from short-lived LLM applications are not. Trace-level observability tools record what each agent said and when; they do not measure whether an agent's internal cognitive state has drifted across weeks, whether two agents have developed measurably different ways of attending to each other,

Chen, Ho Yiing (norika) · Independent Researcher, Taiwan · ORCID 0009-0006-6816-9891