Memory and personality persistency for ai companion agent

The project started in April 2026 and focuses on long-term personality and memory for personal companion agents. It allows your agent to trace a detail — and the feeling attached to it — back to a specific moment, along with the reason why that memory was formed in the first place. **• Evolving personality** — long-term interaction gradually reshapes the agent’s sensitivities over a \~180-day timescale **• Grudge-holding** — negative affect decays roughly 8x slower than positive; recovery follows internal dynamics, not conversational cues **• Reads the room** — expression or suppression of built-up feeling is governed by perceived safety in the relationship **• Permanent marks, both ways** — profound events leave lasting imprints, with identical mechanics for positive and negative experiences **• Traceable feelings** — every emotional disposition can be traced to the originating memory, with timestamp and context attached **• Emergent memory** — memories resurface unprompted, weighted by present salience; what has faded stays quiet, what still matters speaks up **• Flashback recall** — an affect spike retrieves the memory behind it: the feeling arrives first, the memory follows **• Resonant recall** — the current topic pulls up its kin: “this is like the rent dispute last spring” **• Mood-congruent recall** — a low mood surfaces darker memories, a bright one brighter, mirroring human recall bias **• Associative memory web** — every new memory is checked against the entire history at birth, no recency window; relevance can at most double a faint memory’s reach **• Natural forgetting** — unreinforced memories decay in salience and are eventually retired **• Lived time** — perceives elapsed absence with human-like granularity that coarsens with distance **• Real dreams** — recombines emotionally charged memory fragments during rest, leaving a mood residue with no surfaced cause