@inproceedings{2210189b22c94b0a85e7f2163adc34f2,
title = "Why Adapt RAG for Agile? Challenges, Frameworks, and the Role of Evaluator Agent",
abstract = "This paper proposes the adaptation of Retrieval Augmented Generation (RAG) based systems into Agile Software Development workflows, addressing the need for specialized evaluation methods that align with Agile{\textquoteright}s iterative, feedback driven nature. Through a systematic mapping study of 20 papers, we identify existing evaluation frameworks for RAG systems and explore how they can be applied within Agile settings. The research highlights the role of Evaluator-Agents in aligning the responsiveness of RAG systems, with a focus on Multi-agent AI systems that are more efficient at handling complex, distributed tasks than Single-agent systems. The findings contribute to identify the potential of RAG and its evaluation in facilitating real time feedback and continuous improvement for Agile development.",
keywords = "Agile, AI, Evaluation, Large Language Models (LLMs), Mapping-Study, Multi-agent, Retrieval-Augmented Generation (RAG)",
author = "Khan, \{Ayman Asad\} and Toufique Hasan and Mika Saari and Kemell, \{Kai Kristian\} and Jussi Rasku",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2026.; International Conference on Agile Software Development ; Conference date: 02-06-2025 Through 05-06-2025",
year = "2025",
doi = "10.1007/978-3-032-05799-0\_3",
language = "English",
isbn = "978-3-032-05798-3",
series = "Lecture Notes in Business Information Processing",
publisher = "Springer",
pages = "22--31",
editor = "Sibylle Peter and Martin Kropp and Torgeir Dings{\o}yr and Clare Dillon and Philipp Diebold and Deepti Jain and Lunesu, \{Maria Ilaria\} and Andrea Pinna",
booktitle = "Agile Processes in Software Engineering and Extreme Programming {\textendash} Workshops - XP 2025 Workshops, Revised Selected Papers",
}