Generative AI for Agile Project Management

Shipping software in short, steady iterations is how Dr. Alfred Ang works, so agile delivery is familiar ground. Dr. Ang is a full-stack AI developer, Agentic AI solution architect and corporate trainer, and serves as CTO of Tertiary Infotech Academy Pte Ltd, the Singapore training organisation behind Tertiary Courses. The ai-mms course-registration platform, which runs the Tertiary Courses sites in Singapore, Malaysia and Ghana, is developed and deployed continuously, with every change verified locally and released through an automated pipeline, while AI-LMS-TMS, tertiary-hrms and ai-exams each evolved through many small, user-driven increments. Dr. Ang also built a series of single-file IT project-management Kanban boards used in demonstrations and training, featuring drag-and-drop and keyboard moves, filters, overdue badges, KPI tiles, project status charts and timeline views, along with a real-time polling app and a collaborative pinboard that suit standups and retrospectives. Much of this development is done with AI coding agents and Claude Code skills that Dr. Ang publishes for planning, documentation and quality checks. More than 300 public repositories at github.com/alfredang reflect this rhythm of backlog, build, review and improve. For project managers, Scrum Masters and product owners, that means a trainer who has used generative AI inside real sprints rather than only describing agile in theory. Dr. Ang also understands the human side of agile, having coordinated developers, designers and operations staff through frequent releases, shifting priorities and changing stakeholder requests across multiple sites and products. Dr. Ang is also a PMP-certified project manager and a certified Lean Six Sigma Black Belt, so the AI techniques in this course are anchored in formal project management and process-improvement discipline, and as a Distinguished Toastmaster with many public speaking awards he keeps every session clear and engaging.

Generative AI for Agile Project Management turns that practice into a structured learning path. The first topic, getting started with generative AI for agile, introduces tools such as ChatGPT, Claude and Microsoft Copilot and shows how to prompt them for reliable project outputs. Learners then apply AI to backlogs, user stories and planning, generating well-formed stories with acceptance criteria, splitting epics, estimating effort and preparing for sprint planning. The third topic covers sprints, standups and delivery, using AI to summarise progress, surface blockers, draft stakeholder updates and manage risks. The final topic focuses on reporting, retrospectives and improvement, where AI helps analyse sprint data, facilitate retrospectives and capture actionable lessons. Dr. Ang demonstrates each technique with the Kanban boards, dashboards and AI-assisted workflows used in-house, then has participants practise on a realistic project scenario from backlog to retrospective. The teaching style is practical and conversational, with frank discussion of where AI speeds up ceremonies and documentation and where team judgement, facilitation and trust remain irreplaceable. Project managers, Scrum Masters, product owners and team leads will leave with a library of prompts and templates for every stage of the sprint cycle and a clear plan for introducing AI into their team responsibly. Learners also explore how to use AI to keep the definition of done, sprint goals and team agreements visible, and how to prevent AI-generated documentation from replacing genuine conversation between team members. Templates for stand-up summaries and sprint reviews are included. To explore the Kanban boards and agile delivery tools referenced in class, visit Dr. Ang's portfolio at https://github.com/alfredang.