Attacks the core long-context bottleneck — KV cache memory growing linearly with context length — arguing existing KV-cache compression either degrades quality or fails to scale. Proposes an end-to-end compression approach that holds up at scale. High-value for any builder running long-context inference where memory, not compute, is the wall.