Building Kernel Memory Protocol: Navigable Memory for AI Agents

The hard part with many AI agents is not the amount of text in the prompt. The hard part is that they do not have memory they can query, traverse, and audit. Most current approaches try to solve this in one of three ways: copying parts of previous conversations into the next prompt; searching similar chunks with embeddings; letting an agent framework store memory internally, often in a way that is hard to inspect, replay, or explain. Those approaches help, but they are not enough when an agent i