Honestly, the bigger miss is people treating JL as some silver bullet for "extreme" compression, as if preserving pairwise distances for a fixed point set somehow means you still keep the task-relevant structure once you're dealing with modern models.

Try projecting embeddings this way and watch your recall crater the moment you need downstream task performance instead of nearest-neighbor retreival demos. If you're optimizing for blog post vibes instead of anything measurable sure, call it a breakthrough.