agent memory

Conversations and agent tasks outgrow the context window, and naive 'stuff the whole history' fails on cost, latency, and lost-in-the-middle. The signal is a tiered memory design: recent buffer, summarized mid-term, retrieved long-term.

Agents need memory beyond the context window, and 'just store the history' is the wrong answer. The signal is distinguishing the memory types and mapping each to a storage and retrieval strategy. Here is the answer.

A context window is not memory. Real agents need a storage architecture: working buffer, episodic recall, and consolidated facts. The signal is the read/write paths and how you keep memory from rotting.

Cross-session memory is what makes an assistant feel personal, and it is mostly a retrieval and state-management problem, not a bigger context window. The signal is the tiered architecture plus what to store, forget, and protect.