This OER introduces students to designing and developing AI-powered assistants for agile software development using Flowise (no code). Learners as a team explore Retrieval Augmented Generation (RAG) and agent-based systems, applying AI to real-world agile practices while considering technical design, evaluation, and cost-aware decision-making
Benefit of this resource and how to make the best use of it
This resource provides an authentic, project-based approach to learning how AI can support agile software development practices. It enables students to apply concepts such as Retrieval-Augmented Generation (RAG), AI agents, workflow design, and responsible AI adoption within realistic software engineering scenarios. By working within budget and technical constraints, learners also develop critical thinking, teamwork, and decision-making skills valued in industry.
In academic settings, educators can integrate the resource into software engineering, agile development, AI, or computing modules as a group project, capstone activity, or practical assessment. Academic developers and instructional designers may adapt the example use cases to suit different disciplines or institutional contexts, encouraging interdisciplinary collaboration and experimentation with emerging AI tools. The resource can also be modified to focus on specific agile activities, such as requirements engineering, quality assurance, or project management, allowing flexibility to align with diverse learning outcomes and levels of study.
?
This citation is automatically generated and may require adjustment. Always verify it against your style guide.
Giblin, M., & Fallon, S. (2026). Ai powered assisstant for agile software design. National Resource Hub (Ireland). Retrieved from: https://hub.teachingandlearning.ie/resource/ai-powered-assisstant-for-agile-software-design/ License: Creative Commons Attribution-NonCommercial (CC BY-NC).
Adapting this resource? Share your version!
If you have modified or adopted this resource, share your version here. Tracking adaptations helps us measure impact and connects others with useful updates.
The Technological University of the Shannon (TUS) Compendium of Approaches to Integrating Digital Competencies into the Curriculum exemplifies the University’s commitment to embedding digital capability development across teaching, learning, and assessment.
A 1-page guide, co-created by lecturers, tutors & students on DkIT's MA in Learning and Teaching, showing where GenAI can, and can't, support particular postgraduate research/skill development (*reflecting practice 2025-26). Includes student-informed prompts on responsible, sustainable use. An editable PowerPoint supports adaptation to own context.
MTU researchers, together with national and international researchers, presented local, national, and global insights into the challenges and opportunities of assessment and feedback in work placement settings.
Teaching and Assessment for Learning Checklists aimed at early career & seasoned lecturers. The checklists provide guidance & reliable curated resources for lecturers who want to deliver an engaging and positive learning experience for their students. They act as a guide to check existing approaches, and help analyse how improvements can be made.