content & syllabus
Chapter 1 – Fundamentals of GenAI and Prompt Engineering
- Understand what GenAI is and isn’t—no jargon, just practical models
- Learn the basics of prompting and how LLMs work
- 5 demos/hands-on exercises
- 🛠 Outcome: Robust mental model of LLM behavior and basic prompting patterns
Chapter 2: Prompt Engineering As Applied to Requirements Engineering
- Discover structured prompting techniques by trying out various reusable patterns
- Use GenAI for RE-specific scenarios: empathy mapping, devil’s advocacy, conflict resolution
- 8 exercises
- 🛠 Outcome: Prompts that think critically, not blindly follow
Chapter 3 – GenAI and Requirements in Natural Language
- Translate vague requirements into clear, testable text
- Practise phrase templates and glossary building
- 5 exercises
- 🛠 Outcome: AI that improves clarity, and does not create confusion
Chapter 4 – GenAI and Requirements as Models
- Generate diagrams from prompts using PlantUML or Mermaid (Use Case, Class, Activity, State)
- Evaluate which model adds the most value
- 5 exercises
- 🛠 Outcome: Modelling that’s lean, relevant, and iterative
Chapter 5 – GenAI and Quality Characteristics & Constraints in Requirements
- Turn “fast,” “secure,” “intuitive” into measurable, auditable clauses
- Apply standards like OWASP and ISO 25010 in GenAI prompts
- Add a GDPR constraint check as a practical bonus
- 4 exercises
- 🛠 Outcome: AI as a partner in quality, not an exaggerator
Chapter 6 – The Road Ahead
- Discuss hallucinations, outdated data, client confidentiality, and GenAI’s limits
- Learn to scope internal GenAI pilots with a stepwise adoption plan
- Demos and checklists included
- 🛠 Outcome: Realistic roadmap for GenAI adoption in your RE practice
