Generative AI is rapidly changing how software is developed. Rather than merely accelerating isolated coding tasks, a new generation of GenAI tools acts as a development partner that participates across the entire development lifecycle – from ideation and design to implementation, testing, maintenance, and governance. This shift is particularly relevant for service development: digital services must be built and adapted quickly and be continuously refined based on user interaction – exactly the kind of fast-moving, iterative work in which a GenAI development partner can unfold its strengths. 

Realizing these opportunities requires more than access to the technology. Human-GenAI collaboration fundamentally shifts developers' roles and required skills. On the one hand, developers must learn to exploit the advantages of GenAI: delegating suitable tasks to the AI, leveraging its ability to generate solutions remarkably fast, and orchestrating its contributions across the development lifecycle. On the other hand, because GenAI works so quickly and fluently produces output, critical thinking becomes more important than ever: GenAI is inherently uncertain and fallible, so developers must question and validate what the AI produces, explain the decisions behind their work, and take ownership of the result.  

Shaping human-AI collaboration therefore becomes one of the defining challenges of our time. It rests on several key concepts: understanding the complementarity of human and AI strengths and delegating tasks accordingly, designing where to keep a human in the loop, recognizing and handling the uncertainty inherent in GenAI output, and navigating the shift in the skills developers need. 

This course follows an experiential learning approach: Students apply and experience the concepts of human-AI collaboration using AI tools to solve real-world challenges. Rather than studying human-AI collaboration in the abstract, students plan and complete hands-on projects with AI, and they critically reflect on both the result and the collaboration itself as they experience these concepts in their own work. 

As AI tools, students get exclusive access to IBM Bob, which serves as an AI development partner throughout the entire software development lifecycle – from ideation and design to implementation, testing, maintenance, and governance. Besides a systematic understanding of human-AI collaboration, students will acquire practical skills on how to develop software together with GenAI. 

The course is structured around three phases: 

1. Introduction to the concepts of human-AI collaboration through interactive workshops, IBM Bob tutorial 
2. Working phase: In groups, students plan, develop, and evaluate prototypes for real-world innovation challenges in collaboration with IBM Bob, with ad hoc support from the teaching team. 
3. Presentation and report: Student groups present and report on their innovation projects, including a demonstration of their prototype and a reflection of human-AI collaboration concepts. Report is due at the end of the semester; Presentation and report will be graded.