what does ai actually add to open-ended creative work? my first attempt at giving it a process signature: from a real project's transcripts i pulled 146 ideation events; the cubes are the moments ai forked the ideas open, laid along a 3d chronological trace of the sessions.
Kat ⊷ the Poet Engineer@poetengineer__things i find severely lacking in current llm benchmarks but i feel are important for iterative, open-ended knowledge work: - problem-setting. a major part of creative/exploratory work is defining what the problem even looks like. benchmarks skip that and hand you the problem pre-formed. it's the same issue with using exams to predict how someone handles real world problems.