玛丽，玛丽，真拧巴，你的智能体到底能活多久？
像 Grok Bot 和其他元级“套件”这样的新产品，要求我们去创建智能体。那它们应该活多久？
当你设计一个日历智能体时，它的会话应该运行多长时间？是应该在你任职一家公司的整整五年里一直存活，还是每天重置一次？
越来越强大的模型诱惑我们去构建永不关闭的永久会话。但长时间运行的会话会从内部开始腐烂。
随着对话轮次不断累积，注意力会退化。现代模型很容易在长文档中找出单个事实。但研究表明，即使在前沿模型中，智能体的记忆也像人类记忆一样：随着增长而退化。¹
临时指令会变成永久的“幽灵”。三月份告诉你的机器人“这周我感冒了，取消早上的会议”，到了十一月它还在避开早上的时段。
长会话也会破坏安全性。一个对你的收件箱和日历拥有多年读写权限的智能体，就是一道敞开的大门。一封恶意邮件或一个日历邀请就可能污染整个对话，在几个月后悄悄劫持你的日程安排。²
制胜的模式很简单：给你的日常助手一个 24 小时的生命周期，并把具体任务委派给窄领域的专职智能体。
每日重置符合人类实际的工作方式。白天，你的助手记住即时上下文：“我迟到了十五分钟”，或者“留出两到三个空闲时段用于准备”。午夜时分，活跃的对话被彻底清空，让第二天从零开始。
当有工作需要完成时，日常协调者会把任务交给单一用途的帮手：一个日历智能体去安排日程，一个邮件智能体去起草回复，或者一个新闻智能体去搜索网络。每个帮手只存活三十秒，只拥有它需要的特定工具，完成任务后就消失。³
对于日常协调者来说，系统提示词充当调度员的角色：
You are Tomasz's daily coordinator.
Your session lives for 24 hours.
Workflow:
- Morning: Load preferences from `preferences.md`
& today's calendar.
- Intraday: Do not execute directly. Delegate
to sub-agents (`calendar_bot`, `email_bot`).
- Night: At midnight, save durable learnings
to `preferences.md` and terminate.
对于日历帮手来说，系统提示词是一个无状态执行器：
You are an ephemeral calendar specialist.
Process this single request, call the tool,
report the result, & terminate.
Rules:
- Time zone: America/Los_Angeles.
- Duration: 30 minutes.
- Hours: 9:00 AM – 6:00 PM.
- Always check availability first.
Never double-book.
- If full, propose 2 nearest openings & stop.
Output: Return event title, time, & attendees,
then exit.
在一天的会话于午夜被清空之前，会运行一次快速的整合处理。一个离线摘要器回顾这一天，将持久的偏好（“Tomasz 更喜欢三十分钟的会议”）保存到磁盘上的永久笔记中，并丢弃其余日常对话的琐碎内容。⁴
Grok Bot 或你的聊天助手会自动执行这种睡眠周期吗？
目前还不会。大多数机器人会让对话线程永远保持打开状态，直到你点击“+ 新建聊天”，或者上下文压缩悄悄抹掉你的规则。
那首童谣问的是花园的事：银铃花与鸟蛤壳，整整齐齐排成行。那些持久存在的东西，按照某人选择的顺序排列。对智能体而言，答案是一样的：丢掉对话；把规则保存在文件里，让你的智能体和它的花园保持健康。
-
Amirali Ebrahimzadeh 和 Seyyed Muhammad Salili，《并非所有针都能找到：事实分布与提示方式如何影响长上下文大语言模型的推理》，arXiv:2601.02023，2026 年 1 月；Kelly Hong 等人，《上下文腐烂：输入 token 增加如何影响大语言模型性能》，Chroma Research，2025 年。↩︎
-
《大语言模型智能体中的休眠记忆投毒》，arXiv:2605.15338，2026 年 5 月。该研究展示了有状态 AI 助手中持久存在的跨会话记忆投毒攻击。↩︎
-
Shiyang Chen，《治理衰退：上下文压缩如何在长周期大语言模型智能体中悄然抹除安全约束》，arXiv:2606.22528，2026 年 6 月。该研究表明，压缩操作在 30–59% 的会话轮次中会丢弃既定规则。↩︎
-
Anthropic，《梦境：记忆巩固》，研究预览 dreaming-2026-04-21，2026 年 4 月；以及 Letta v2 有状态智能体框架（2026 年）。↩︎
Mary, Mary, quite contrary, how long do your agents live?
New products like Grok Bot & other meta-harnesses ask us to create agents. How long should they live?
When you design a calendar agent, how long should its session run? Should it stay alive for your entire five-year tenure at a company, or reset every day?
Ever more powerful models tempt us to build perpetual sessions that never close. But long-running sessions rot from the inside out.
As conversational turns pile up, attention degrades. Modern models easily spot a single fact in a long document. But research shows even across frontier models, agent memory is like human memory : it degrades as it grows.1
Temporary commands turn into permanent ghosts. Tell your bot in March, “I have a cold this week, cancel morning meetings,” & by November it is still avoiding morning slots.
Long sessions also break security. An agent holding multi-year read & write access to your inbox & calendar is an open door. One malicious email or calendar invite can poison the conversation, quietly hijacking your schedule months down the road.2
The winning pattern is simple : give your daily assistant a 24-hour life, & delegate individual tasks to narrow specialists.
A daily reset matches how humans actually work. During the day, your assistant remembers immediate context : “I’m running fifteen minutes late,” or “keep two to three free for prep.” At midnight, the active conversation wipes clean so tomorrow starts fresh.
When work needs doing, the daily coordinator hands the job to a single-purpose helper : a calendar agent to schedule, an email agent to draft a reply, or a news agent to search the web. Each helper lives for thirty seconds with only the specific tools it needs, does the job, & disappears.3
For the daily coordinator, the system prompt acts as a dispatcher :
You are Tomasz's daily coordinator.
Your session lives for 24 hours.
Workflow:
- Morning: Load preferences from `preferences.md`
& today's calendar.
- Intraday: Do not execute directly. Delegate
to sub-agents (`calendar_bot`, `email_bot`).
- Night: At midnight, save durable learnings
to `preferences.md` and terminate.
For the calendar helper, the system prompt is a stateless executor :
You are an ephemeral calendar specialist.
Process this single request, call the tool,
report the result, & terminate.
Rules:
- Time zone: America/Los_Angeles.
- Duration: 30 minutes.
- Hours: 9:00 AM – 6:00 PM.
- Always check availability first.
Never double-book.
- If full, propose 2 nearest openings & stop.
Output: Return event title, time, & attendees,
then exit.
Before the day’s session wipes at midnight, a quick consolidation pass runs. An offline summarizer reviews the day, saves lasting preferences (“Tomasz prefers thirty-minute meetings”) into a permanent note on disk, & throws away the rest of the daily chatter.4
Does Grok Bot or your chat assistant perform this sleep cycle automatically?
Not today. Most bots leave threads open forever until you click “+ New Chat” or context compaction silently erases your rules.
The nursery rhyme asks about a garden : silver bells & cockle shells, all in a row. Things that persist, in an order someone chose. The answer for an agent is the same : throw away the conversation ; keep the rules in a file to keep your agent & its garden healthy.
-
Amirali Ebrahimzadeh and Seyyed Muhammad Salili, “Not All Needles Are Found: How Fact Distribution and Prompting Shape Inference in Long-Context LLMs,” arXiv:2601.02023, January 2026; Kelly Hong et al., “Context rot: How increasing input tokens impacts LLM performance,” Chroma Research, 2025. ↩︎
-
“Sleeper Memory Poisoning in LLM Agents,” arXiv:2605.15338, May 2026. Demonstrates persistent cross-session memory poisoning attacks in stateful AI assistants. ↩︎
-
Shiyang Chen, “Governance Decay: How Context Compaction Silently Erases Safety Constraints in Long-Horizon LLM Agents,” arXiv:2606.22528, June 2026. Demonstrates that compaction drops standing rules in 30–59% of episodes. ↩︎
-
Anthropic, “Dreams: Memory Consolidation,” research preview
dreaming-2026-04-21, April 2026; and the Letta v2 stateful agent framework (2026). ↩︎