一句话：提出 Onboarding Buddy，用 LLM、检索增强生成与思维链的多智能体系统为开发者提供上下文相关的入职指导。
软件工程中的入职（onboarding）因技术快速演进而困难重重，传统探索式学习与集中培训成本高、耗时长且易过时。本文提出 Onboarding Buddy 系统，基于大语言模型、检索增强生成（RAG）以及自动化思维链（chain-of-thought）推理，构建面向开发环境的智能体式助手，可提供自然语言解释、代码洞察与项目导航，并以极少人工干预实现个性化支持。该系统与 GitHub Copilot 等工具类似，但独特之处在于将思维链推理机制与检索增强生成结合，专门面向动态的入职场景。作者在单个项目中对 8 名参与者开展初步评估，助手有用性评分为 M=3.26（SD=0.86），入职易用性为 M=3.0（SD=0.96）（满分 4 分）。作者指出该评估规模有限，未来将在更大团队和多个真实代码库中验证其更广泛的适用性，认为该工具有望提升开发者生产力与满意度。
Effective onboarding in software engineering is crucial but difficult due to the fast-paced evolution of technologies. Traditional methods, like exploration and workshops, are costly, time-consuming, and quickly outdated in large projects. We propose the Onboarding Buddy system, which leverages large language models, retrieval augmented generation, and an automated chain-of-thought approach to improve onboarding. It integrates dynamic, context-specific support within the development environment, offering natural language explanations, code insights, and project guidance. Our solution is agent-based and provides customized assistance with minimal human intervention. Our study results among the eight participants show an average helpfulness rating of (M=3.26, SD=0.86) and ease of onboarding at (M=3.0, SD=0.96) out of four. While similar to tools like GitHub Copilot, Onboarding Buddy uniquely integrates a chain-of-thought reasoning mechanism with retrieval-augmented generation, tailored specifically for dynamic onboarding contexts. While our initial evaluation is based on eight participants within one project, we will explore larger teams and multiple real-world codebases in the company to demonstrate broader applicability. Overall, Onboarding Buddy holds great potential for enhancing developer productivity and satisfaction. Our tool, source code [7], and demonstration video [6] are publicly available.
@inproceedings{paperbot8949,
title = {A Multi-agent Onboarding Assistant based on Large Language Models, Retrieval Augmented Generation, and Chain-of-Thought},
author = {Andrei Cristian Ionescu and Sergey Titov and Maliheh Izadi},
booktitle = {FSE},
year = {2025},
doi = {10.1145/3696630.3728611}
}