Lossless long-term memory for a personal AI — never summarize, keep every line, and put a timestamp on everything. Most long-term memory systems for AI do one of two things: they summarize conversations into compact notes, or they embed them and retrieve "similar" chunks. Both lose the thing that matters most to a person who talks to the same AI every day: what was actually said, and when. This project takes the opposite position. Keep every line. Raw conversation logs are stored in full. Nothing is summarized, ever. Summaries are a map; the log is the territory. Timestamp everything. Every record — utterance, action, document chunk — carries a timestamp, and every index is built on top of that time axis. We call this the Temporal Backbone . Search by time first, words second. "Yesterday evening, about the budget" is a valid query. The time phrase narrows the range; the words rank within it. Results come back in chronological order, unsummarized, with their timestamps. Inject "where we are" every turn.…