AWS 推出 AgentCore 记忆生命周期管理方案
原标题：Designing lifecycle policies for AgentCore memory
AI 摘要
AWS 在机器学习博客中介绍了 AgentCore 记忆的生命周期管理方案，针对长期运行的 AI 代理（如客服、销售顾问）因记忆累积导致上下文过时和合规风险的问题，提出了基于记忆类型（情景、语义、程序）的三种生命周期策略：TTL 过期、相关性衰减评分和整合修剪。方案使用 AWS Step Functions 和 Amazon Bedrock 实现夜间工作流，并提供了 AWS CDK 部署代码。该方案旨在通过系统化管理记忆，提升代理响应质量并降低合规风险。
正文节选
Designing lifecycle policies for AgentCore memory Memory lifecycle policies help long-running agents on Amazon Bedrock AgentCore stay effective by systematically managing what they remember and forget. Your agent generates memories from every conversation it conducts. If you don’t actively manage these memories, your agents will accumulate outdated context, which can degrade response quality and create compliance risks for your deployment. After months of production use, problems emerge. We obse