AIST | 1 Day
Put GenAI to work across your whole software team, with practical skills tailored to each accountability. This one-day course equips Product Owners, Scrum Masters, and Developers to use AI tools for planning, facilitation, coding, and testing, while staying clear-eyed about the cautions each role faces. You’ll work in teams on a shared case study, putting each technique to use the way a real agile team would.
Who should take this course?
This course is for every member of a software development team, with a special focus on Product Owners/Product Managers, Scrum Masters/Agile Coaches, and Developers. It’s equally valuable for anyone exploring how GenAI fits into agile delivery.
Some software development experience is helpful but not required; familiarity with Agile, Scrum, and GenAI tools is beneficial, and attendees should have access to tools such as ChatGPT, Gemini, Microsoft Copilot, and/or GitHub Copilot.
Course Content
This course progressively builds your fluency with GenAI tools, from understanding AI and prompt engineering to applying it across the Product Owner, Scrum Master, and Developer accountabilities. You’ll work hands-on in teams on a shared case study, the way a real agile team would.
1. What is AI?
- AI introduction and types
- Generative and Predictive AI
- Popular AI tools
- Prompt engineering and proven practices
- Agile Manifesto implications
- Team-based, hands-on activities
2. AI for Product Owners / Product Managers
- Case study kickoff
- Product Owner accountabilities and stances
- AI tools for strategic planning and vision
- AI tools for understanding the audience
- AI tools for planning, tracking, and execution
- Cautions for Product Owners
- Team-based, hands-on activities
3. AI for Scrum Masters / Agile Coaches
- Scrum Master accountabilities and stances
- AI tools for guidance and growth
- AI tools for process and progress
- AI tools for transformation and advocacy
- Cautions for Scrum Masters
- Team-based, hands-on activities
4. AI for Developers
- Developer accountabilities and stances
- AI tools for code analysis, testing, and improvement
- AI tools for documentation and explanation
- AI tools for maintainability and optimization
- Cautions for Developers
- Team-based, hands-on activities