A Multi-agent Onboarding Assistant based on Large Language Models, Retrieval Augmented Generation, and Chain-of-Thought
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 Traditional methods, like exploration and workshops, are costly, time-consuming, and quickly outdated in large projects.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.
Wed 25 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
14:00 - 15:30 | AgentDemonstrations / Industry Papers / Research Papers at Cosmos 3B Chair(s): Chunyang Chen TU Munich | ||
14:00 10mTalk | A Multi-agent Onboarding Assistant based on Large Language Models, Retrieval Augmented Generation, and Chain-of-Thought Demonstrations Andrei Cristian Ionescu Delft University of Technology, Sergey Titov JetBrains Research, Maliheh Izadi Delft University of Technology | ||
14:10 20mTalk | Alibaba LingmaAgent: Improving Automated Issue Resolution via Comprehensive Repository Exploration Industry Papers Yingwei Ma Tongyi Lab, Alibaba, Qingping Yang Tongyi Lab, Alibaba, Rongyu Cao Tongyi Lab, Alibaba, China, Binhua Li Tongyi Lab, Alibaba, China, Fei Huang Tongyi Lab, Alibaba, China, Yongbin Li Tongyi Lab, Alibaba, China | ||
14:30 20mTalk | Demystifying LLM-based Software Engineering Agents Research Papers Chunqiu Steven Xia University of Illinois at Urbana-Champaign, Yinlin Deng University of Illinois at Urbana-Champaign, Soren Dunn University of Illinois Urbana-Champaign, Lingming Zhang University of Illinois at Urbana-Champaign DOI | ||
14:50 20mTalk | AEGIS: An Agent-based Framework for Bug Reproduction from Issue Descriptions Industry Papers Xinchen Wang Harbin Institute of Technology, Pengfei Gao ByteDance, Xiangxin Meng Beihang University, Chao Peng ByteDance, Ruida Hu Harbin Institute of Technology, Shenzhen, Yun Lin Shanghai Jiao Tong University, Cuiyun Gao Harbin Institute of Technology, Shenzhen | ||
15:10 20mTalk | Enhancing Game AI Behaviors with Large Language Models and Agentic AI Industry Papers Ciprian Paduraru Gameloft, and University of Bucharest, Miruna Gabriela Paduraru University of Bucharest
, Alin Stefanescu University of Bucharest | ||
Cosmos 3B is the second room in the Cosmos 3 wing.
When facing the main Cosmos Hall, access to the Cosmos 3 wing is on the left, close to the stairs. The area is accessed through a large door with the number “3”, which will stay open during the event.