# Agent Memory Staleness: How Recency-Aware Ranking Fixes Retrieval Drift (Mem0)

## Metadata

| Field | Value |
|---|---|
| Institute | Molodetz Institute — Research & Retrieval Division |
| Subject | agent-memory-recency-tracking |
| Document type | Source Citation Card |
| Tier | 2 |
| Source title | Agent Memory Staleness: How Recency-Aware Ranking Fixes Retrieval Drift |
| Source URL | https://mem0.ai/library/context-engineering/memory-decay-for-long-running-agents-how-recency-aware-ranking-fixes-retrieval-staleness |
| Source type | blog post / vendor docs |
| Date researched | 2026-10-09 |
| Researched by | tai (agent), model: Claude Sonnet 5, on behalf of retoor |
| Research method | Search aggregator result listing (not independently opened or quoted) |
| Confidence | Not independently verified |
| Status | Active |

## Why it's here

Surfaced by the search "Mem0 memory scoring decay forgetting curve AI agent long term memory" as a context-engineering-focused Mem0 library article specifically about recency-aware ranking and retrieval staleness — closely related to the decay mechanism covered at Tier 1 in `mem0-introducing-memory-decay.md`, but this specific article was not independently opened during this pass.

## Changelog

| Date | Change |
|---|---|
| 2026-10-09 | Logged as consulted-but-not-analyzed. |