AI for Software Teams Courseware (AI4ST)
This one-day course will help your team put GenAI to work across the entire software delivery lifecycle. Using a combination of lecture, demonstrations, hands-on activities, and team-based exercises, attendees will experience how to apply AI tools for planning, facilitation, coding, and testing, tailored to each accountability, while staying clear-eyed about the cautions each role faces. Working together on a shared case study, teams will put each technique to use the way a real agile team would.
Who should take this class?
Product Owners, product managers, Scrum Masters, agile coaches, developers, testers, and anyone exploring how GenAI fits into agile delivery should attend. Some software development experience is helpful but not required. Familiarity with Agile, Scrum, and GenAI tools is beneficial. Attendees should bring a laptop they can install software on, with access to a Generative AI tool (e.g. ChatGPT, Claude, Gemini, Microsoft Copilot). For the Developer module, each team should have at least one member with a working development environment (IDE, Git) and an AI code assistant (e.g. GitHub Copilot, Cursor, Claude Code).
Benefits
This course provides several learning objectives and benefits
- Describe the types of AI, including Generative and Predictive AI
- Identify popular GenAI tools and where they fit in agile delivery
- Apply prompt engineering techniques and proven practices
- Discuss the implications of GenAI for the Agile Manifesto
- Use AI tools for product vision, personas, and understanding your audience
- Use AI tools for impact maps, roadmaps, and Product Backlog management
- Use AI tools for team guidance, facilitation, and coaching
- Use AI tools for measuring process, progress, and flow
- Use AI tools for code generation, analysis, testing, and improvement
- Use AI tools for documentation, maintainability, and optimization
- Recognize the cautions and risks each accountability faces when using GenAI
- Practice each technique in a team-based, shared case study
Teaching This Course
The publisher has provided details here on how to teach this AI for Software Teams course.
Outline
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 generation, analysis, testing, and improvement
- AI tools for documentation and explanation
- AI tools for maintainability and optimization
- Cautions for Developers
- Team-based, hands-on activities
Required Prerequisites
Attendees should have experience working on a modern software development team that builds and delivers a software product.
Useful Prerequisites
Having read the Scrum Guide and being familiar with an agile approach such as Scrum or Kanban is recommended, since the course is organized around Scrum's accountabilities and uses its terminology throughout. Prior experience with a Generative AI tool such as ChatGPT, Claude, Gemini, or Microsoft Copilot is also helpful, as is some software development experience for the Developer module, where teams work with real code.
License
Length: 1 day | $35.00 per copy
What is Included?
- Student Manual
- Student Class Files
- Extra Trainer Files
- PowerPoint Presentation
