LLMs made me do it

The hard part of computer programming isn’t expressing what we want the machine to do in code. The hard part is turning human thinking – with all its wooliness and ambiguity and contradictions – into computational thinking that is logically precise and unambiguous, and that can then be expressed formally in the syntax of a programming language.

The internet challenged copyright by creating infinite distribution of perfect copies. With AI, what happens when infinite distribution is hooked up to infinite imitation?

Another answer is not to cultivate the machine’s output but to compose through it, treating the model as material, choosing the inputs and shaping the rules. In other words, not working beside the machine, but stepping inside it.

A good prompt doesn’t need to function like a blueprint. They can also behave like a horoscope or a fortune.

Lately, I’ve been thinking about my use of AI as a kind of spatial relationship. Where do I stand in relation to the machine—above it, beside it, under it? Each position carries a different kind of power dynamic. To be above is to steer, beside is to collaborate, below is to serve.