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Evidence record 18439 · automatically gathered

Self-evolving Agentic Customer Support System at LinkedIn

Enterprise support agents operate in rapidly changing environments where policies, product capabilities, and knowledge bases evolve continuously, making static assistants brittle and costly to maintain. We present LinkedIn's self-evolving agentic support system, which integrates retrieval-augmented generation with evolutionary auto-prompting and a modular, production-aligned evaluation framework to enable safe, continuous improvement without retraining foundation models. The system treats prompt

Record details

Published: 10 August 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy · Environment
Retrieved: 12 August 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Agents & autonomy · Shared topic: Environment

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Shared topic: Agents & autonomy · Shared topic: Environment

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Shared topic: Agents & autonomy · Shared topic: Environment

DSLE: A Learning Environment for Dark Souls Boss Encounters

arXiv cs.AI · 10 August 2026

Shared topic: Agents & autonomy · Shared topic: Environment

CEAA: A Cognitive Embodied Agents Architecture for Interactive Computing Systems

arXiv cs.AI · 10 August 2026

Shared topic: Agents & autonomy · Shared topic: Environment

OpenLoopEvolve: A Verifiable Self-Evolution Framework for Loop Policies in Long-Horizon Complex Tasks

arXiv · 10 August 2026

How to cite this record

ethics.ai (10 August 2026), “Self-evolving Agentic Customer Support System at LinkedIn,” evidence record 18439, https://ethics.ai/record/18439 (originally published by arXiv).

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