Summarization Memory

Summarization memory is a pattern where an agent periodically compresses older parts of the conversation into a running summary, then replaces the raw history with that summary in the prompt. This keeps the context window from overflowing while preserving a high-level record of prior exchanges. The quality of recall depends on summary fidelity; key details that fall outside the summary are permanently lost to the model.