memory

My agent's memory only ever grew, so I built a weekly no-agent cron that turns seven days of messages into a ratify-it-myself candidate report.

TL;DR: The author audited their agent's memory files and found everything only accumulates, never gets pruned or corrected. ChatGPT and Letta solve this with out-of-band batch synthesis, so the author built a weekly Python script that generates a candidate report instead. They insist on manual ratification since a single fabricated entry could poison a single-agent setup.

Queries returned just a path and a score. So I stole OpenViking's L0 summary pattern: one line per dossier, no new infrastructure.

TL;DR: Search results in my knowledge base showed only scores, so I kept opening dossiers just to judge relevance. Rather than install OpenViking, I stole its L0 tier pattern and added a mandatory one-line summary field to each dossier in about 40 lines of Python. Making summaries a hard requirement keeps them consistent, no new dependency needed.

ChatGPT memory is not a real-time summary of your sessions. I break down the real mechanism: periodic synthesis, system prompt injection, and the privacy cost.

TL;DR: ChatGPT doesn't scan your chat history with RAG. Instead, it periodically synthesizes your conversations into a static profile injected into every new session's system prompt, including roughly your last 40 typed messages. Since deleting one chat won't erase derived insights, treat memory as a managed archive, not a perfect record.