# Amazon — Designing lifecycle policies for AgentCore memory

- Company: Amazon (amazon.com)
- Announced: 2026-09-04T17:20:04+00:00
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://aws.amazon.com/blogs/machine-learning/designing-lifecycle-policies-for-agentcore-memory/
- Record: https://forck.live/items/8388-designing-lifecycle-policies-for-agentcore-memory
- Subject: Bedrock / Nova

Amazon Web Services introduced memory lifecycle management for AI agents using AgentCore memory on Amazon Bedrock, with a deployable architecture using AWS Step Functions and Amazon Bedrock to run nightly lifecycle workflows. The solution includes TTL-based expiration, relevance decay scoring, and consolidation policies to manage agent memories.

## Evidence

Verbatim from https://aws.amazon.com/blogs/machine-learning/designing-lifecycle-policies-for-agentcore-memory/:

> In this post, we introduce memory lifecycle management for AI agents: the practice of systematically scoring, consolidating, and pruning agent memories over time. We walk through a deployable architecture using AgentCore memory (a capability of Amazon Bedrock AgentCore), AWS Step Functions, and Amazon Bedrock to run a nightly lifecycle workflow.

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