Will be presented at:
Domain specific languages (DSLs) of live coding define their grammar and abstraction level, which in turn determine what can be manipulated during a performance. It is possible to create one-line abstractions specifying, for example, bpm, instruments, beats and accents. When used for live coding, machine learning is capable of creating agents with varying degrees of agency as well as large language models, trained to write code (e.g. in SuperCollider), adding another abstraction level. Many DSLs have been developed during the last ten years. This manuscript proposes three concepts from which we can analyze DSLs: resistance, emergence and community. Resistance encompasses the technical constraints and physicality of the machines, emergence is understood as the possibility of finding something unexpected and community includes the colective and political aspects of live coding. I will argue that we can learn a lot about the nature of live coding by looking at the abstractions and possibilities of DSLs by analyzing them through these ideas.