This paper presents a study of a group of university students using generative machine learning to translate from natural language to computer code. The study explores how the use of the AI tool can be understood in terms of co-creation, focusing on the one hand on how the tool may serve as a resource for understanding and learning, and on the other hand how the tool affects the creative processes. Findings show how the participants search for a 'correct' syntax in their instructions to the machine learning tool, and how the inconsistent and erroneous behavior can work as a way to generate clues and inspiration for generating creative expressions. The notion of friction is used to describe how systems like this can serve to both lower thresholds for programming, and also interfere with the creative processes, encouraging reflection and exploration of alternative solutions.