In The Evolution of Agent Memory I argued that once an LLM becomes the brain of an agent, context management becomes unavoidable: interactions pile up, the window eventually fills, and something has to go. Today’s mainstream answers are two — truncate the oldest text and re-prefill what’s kept, or selectively evict tokens by importance. This post is about a third path, and it’s training-free: take the KV cache you prefilled over the full context, slice it down to a subset, and use that — it is often more accurate than recomputing from the same kept text. Note that the two arms keep the exact same text; the only difference is where the KV came from. ...