V · MemoryExperimental·

Five-Tier Memory Cascade

also known as Multi-Tier Memory, Cognitive Memory Hierarchy

Stage agent memory across sensory, working, short-term, episodic, and long-term tiers with explicit promotion and decay between them.

Context

A long-running agent accumulates information at very different timescales. Some observations are one-tick-only ('the user just clicked save'); some are one-day patterns ('this user worked on project X this afternoon'); some are one-month rules ('this user prefers concise replies'); some are stable identity facts ('this user's name is Marco'). A flat single-tier memory store cannot represent these differences in age, decay rate, or relevance horizon.

Problem

A flat append-only log collapses signal across timescales: a momentary observation and a stable identity fact look the same and compete for attention. Pure long-term memory, on the other hand, cannot capture momentary salience — a recent flick of attention that needs to live for the next few minutes and then expire. Without an explicit cascade that separates working memory from short-term, episodic, semantic, and long-term tiers, each with its own decay and promotion rules, the agent either drowns in stale recent noise or forgets the very fast signals it needs in order to respond well.

Forces

  • Promotion criteria from one tier to the next must be defined and audited.
  • Storage cost grows with tier count.
  • Reads must consult the right tier; cross-tier conflicts must be resolved.

Example

A personal agent that runs continuously needs to track the user's last sentence (sensory), the current task (working), today's session (short-term), the last few weeks of episodes (episodic), and stable preferences (long-term). A flat append-only log either grows unboundedly or loses the immediate signal. The team builds a Five-Tier Memory Cascade with explicit promotion (today's confirmed preference moves to long-term) and decay (yesterday's sensory buffer is dropped). Each tier serves the timescale it's good at.

Diagram

Solution

Therefore:

Five tiers. Sensory: raw input per tick. Working: top-N items in active focus (Global Workspace Theory, ≤7 items). Short-term: recent verbatim (1-7 days). Episodic: compressed summaries (5-10x). Long-term: distilled rules and insights. Compaction promotes upward on a schedule; decay archives downward; rehearsal lifts archived items back when re-attended.

What this pattern forbids. Reads at each tier may only return items at that tier's compaction level; cross-tier joins go through promotion or rehearsal.

The smaller patterns that complete this one —

And the patterns that stand alongside it, or against it —

  • composes-withAppend-Only Thought Stream★— Make the agent's thought log append-only so the agent cannot rewrite its own history.
  • alternative-toMemGPT-Style Paging★— Treat the LLM context window as RAM and external storage as disk, with the model issuing tool calls to page memory in and out.
  • composes-withSalience Attention Mechanism★— Score every candidate memory item with a weighted salience function so each tick attends to a small, relevant top-k subset rather than re-reading all memory.
  • complementsPreoccupation Tracking★— Maintain a small set of mid-term, affect-tagged concerns that persist across days and surface in every prompt, distinct from the single-item working focus and from long-term insights.

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References

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