AI for Software Requirements and User Story Generation Training Course
This practical course explores how generative AI can be leveraged to convert stakeholder feedback into organized requirements, epics, user stories, and acceptance criteria, all tailored for Agile development environments.
Designed for beginner-level product and project professionals, this instructor-led live training (available online or on-site) focuses on using tools such as ChatGPT or Claude to enhance clarity, efficiency, and traceability during the requirement gathering and refinement phases.
Upon completion, participants will be able to:
- Apply AI prompts to collect and refine business requirements.
- Transform feature requests into well-structured user stories and epics.
- Utilize AI assistance to generate acceptance criteria, identify edge cases, and define "done."
- Work effectively with development teams using documentation structured by AI.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical application.
- Hands-on implementation within a live-lab setting.
Customization Options
- For customized training needs, please contact us to make arrangements.
Course Outline
Introduction to AI in Requirements Engineering
- Overview of AI tools for product teams
- Understanding the role of requirements in Agile and Scrum
- Benefits and limitations of using AI for requirement capture
Gathering and Structuring Requirements with AI
- Interview simulation with AI: transforming verbal input into requirements
- Prompting techniques to clarify ambiguous statements
- Organizing requirements into themes and features
Generating User Stories and Epics
- Converting plain text into actionable user stories
- Using AI to identify actors, actions, and goals
- Creating epics and story hierarchies from AI suggestions
Writing Acceptance Criteria and Edge Cases
- Generating Given-When-Then testable criteria
- Identifying exception paths and boundary conditions with AI
- Reviewing AI outputs for clarity and completeness
Refinement and Story Grooming with AI
- Summarizing stakeholder meetings and notes
- Splitting and merging stories using prompt guidance
- Automating backlog refinement with AI assistance
Collaboration and Handoff
- Sharing AI-generated stories with developers
- Ensuring traceability from feature to test case
- Generating documentation for stakeholder sign-off
Summary and Next Steps
Requirements
- Fundamental knowledge of software project lifecycles
- Familiarity with Agile or Scrum frameworks
- No prior technical background required
Target Audience
- Product Owners
- Business Analysts
- Scrum Masters
Open Training Courses require 5+ participants.
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Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
Michal Maj - XL Catlin Services SE (AXA XL)
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