AI and Agile Software Development: From Frustration to Success - XP2025 Workshop Summary

Programming Methodologies: Agile, Scrum, and Devops in Practice

Modern software development requires flexible, efficient, and collaborative methodologies to cope with rapidly changing requirements and complex systems. This article explores three widely adopted programming and software development methodologies: Agile, Scrum, and DevOps. Agile focuses on iterative development, customer collaboration, and continuous improvement. Scrum, as an Agile framework, provides structured roles, events, and artifacts to enhance team productivity and project transparency. DevOps extends Agile principles by integrating development and operations, enabling continuous integration, continuous delivery, and faster deployment cycles. Through practical analysis and real-world examples, this study highlights how these methodologies complement each other in practice, improve software quality, reduce time-to-market, and enhance collaboration among stakeholders. The article concludes by discussing best practices and challenges in adopting Agile, Scrum, and DevOps in modern software engineering environments.

Development Activities: Perspectives of Agile Practitioners

Operationalizing the EU AI Act in Agile Software Development: A Guideline-Based Approach

Context: The EU AI Act requires providers and deployers of Artificial Intelligence (AI) systems to implement documentation, risk management, and human oversight. Agile teams that ship AI features in short iterations lack specific artifacts to discharge these duties, since the regulation's abstract provisions do not map onto the Definition of Done, Sprint Reviews, or working agreements. Objective: We provide agile teams with an actionable compliance instrument: an evaluated guideline that operationalizes EU AI Act obligations as activities integrable into existing agile practice. We further document the translation method behind it so that the approach can be reused for adjacent regulations. Method: Following Design Science Research, we assessed each EU AI Act article along three dimensions. We subsequently classified the articles using a traffic-light scheme and mapped those deemed highly relevant to previously documented pain points of agile teams working with AI. We validated the resulting catalog with practitioners through a survey and 11 additional semi-structured expert interviews, analyzed via qualitative content analysis. Results: The guideline comprises 12 items covering roles and responsibilities, risk and quality management, transparency and traceability, monitoring, and regulatory sandboxes. Practitioners rated the catalog as understandable and relevant; feasibility varied with organizational maturity. Effective adoption towards EU AI Act compliance requires collective ownership across roles and integration into existing agile events rather than parallel compliance processes. Conclusions: The catalog gives agile teams a starting point to transform their delivery practices towards an EU AI Act compliance without dismantling agile practices.

Software Development Methodologies Evolutionary Trends from Waterfall to DevOps

Agile and DevOps are currently the most popular software development techniques. Software methodologies started with the application of the Waterfall model and other models of Software development. It provides a general overview of the approaches and their integration throughout the Software Development Life Cycle (SDLC). SDLC phases are described and different SDLC methodologies are discussed with respect to their impact on motivation, productivity and quality. A comparison of the traditional Waterfall and newer iterative/incremental/agile is identified, as are the reasons behind this change, such as customer participation, timely feedback, and quality improvement. The following issues are common to all methodologies: architecture limitations, scalability and organizational restrictions. It was identified that the industry tends to follow a hybrid Agile-DevOps practice with more emphasis on automation, continuous integration and collaboration to achieve quick and competitive software environments.

A Comprehensive Systematic Literature Review of Agile Methodology

Agile methodology, which offers collaborative, adaptable, and iterative alternatives to conventional plan-driven procedures, has become a revolutionary paradigm in project management since it was codified in the Agile Manifesto. Agile was first used in software development, but it has now spread across many different industries, demonstrating its increasing applicability in dealing with complexity, ambiguity, and quick environmental change. Given this expansion, a comprehensive synthesis of the existing body of knowledge is necessary to understand the trajectory of Agile’s development, its practical applications, and its theoretical foundations. The literature demonstrates enduring issues, such as organizational resistance, misalignment with current governance structures, and the shortcomings of traditional performance measuring tools, despite widespread implementation. As a result, hybrid models that combine Agile and conventional methods have drawn more academic and real-world interest. This paper aims to present a literature review of Agile methodologies from 2001 to 2025, systematically examining their evolution, cross-sectoral diffusion, and key adaptations. It further identifies critical gaps in the literature and outlines future research directions, particularly in relation to sustainability, emerging market contexts, and the advancement of hybrid frameworks. Through this analysis, the study aims to provide a coherent and integrated understanding of Agile’s role in managing complexity and enhancing value delivery in contemporary organizational environments.

Combining Low-Code Platforms with Traditional Software Engineering for Agile Development

The integration of low-code platforms with traditional software engineering practices presents a transformative approach to agile development. Low-code platforms enable rapid application development through visual interfaces and minimal coding, fostering increased collaboration and faster time-to-market. However, challenges such as limited customization and potential technical debt necessitate the involvement of experienced software engineers. This paper explores the synergies between low-code platforms and traditional development methodologies, proposing a hybrid model that leverages the strengths of both. We examine case studies where this integration has led to improved development efficiency and product quality, and discuss best practices for implementing this combined approach in agile environments.