The proliferation of large language models (LLMs) and their integration into multi-agent systems has paved the way for sophisticated automation in various domains. This paper introduces AutoGenesisAgent, a multi-agent system that autonomously designs and deploys other multi-agent systems tailored for specific tasks. AutoGenesisAgent comprises several specialized agents including System Understanding, System Design, Agent Generator, and several others that collectively manage the lifecycle of creating functional multi-agent systems from initial concept to deployment. Each agent in AutoGenesisAgent has distinct responsibilities ranging from interpreting input prompts to optimizing system performance, culminating, in the deployment of a ready-to-use system. This proof-of-concept study discusses the design, implementation, and lessons learned from developing AutoGenesisAgent, highlighting its capability to generate and refine multi-agent systems autonomously, thereby reducing the need for extensive human oversight in the initial stages of system design. Keywords: multi-agent systems, large language models, system design automation, agent architecture, autonomous systems, software deployment

翻译：大语言模型（LLMs）的普及及其与多智能体系统的融合，为各领域的复杂自动化开辟了道路。本文提出AutoGenesisAgent——一种能够针对特定任务自主设计并部署其他多智能体系统的智能体系统。该系统包含系统理解、系统设计、智能体生成器等多个专用智能体，它们协同管理从初始概念到部署的完整多智能体系统生命周期。每个智能体在AutoGenesisAgent中承担独特职责，涵盖从输入提示解析到系统性能优化等环节，最终部署立即可用的系统。本概念验证研究探讨了AutoGenesisAgent的设计、实现及开发经验，重点展示其自主生成与优化多智能体系统的能力，从而减少系统设计初期对人工干预的依赖。关键词：多智能体系统；大语言模型；系统设计自动化；智能体架构；自主系统；软件部署