# arXiv 论文提出运行时无关的持久智能体架构，可跨模型、harness 和主机迁移

- 来源：elvis (@omarsar0)
- 发布时间：2026-09-03 08:00
- AIHOT 分数：45
- AIHOT 链接：https://aihot.virxact.com/items/cmtkrqw6b03kgroalpww4m7vm
- 原文链接：https://x.com/omarsar0/status/2095300793561931948

## AI 摘要

一篇 arXiv 论文（https://arxiv.org/abs/2609.00546）提出一种运行时无关的持久智能体架构，把智能体拆为持久的身份、私有记忆和带版本历史的代码，以及可替换的模型、harness、宿主服务器和交互界面。

## 正文

What a super interesting paper this one is.

They propose an architecture for agents that outlive their model, harness and host.

Today we describe an agent by whatever model and harness it happens to run on. That works for a single session. It says very little about an agent that runs for months and gets moved to a new model, a new harness, or a new machine along the way.

The paper splits an agent in two.

One half is the agent itself, and it persists. Its identity, its private memory, and its own code with version history.

The other half is plumbing you can replace. The model doing the reasoning, the harness running it, the server hosting it, and the ways people reach it such as chat, an API, or a UI.

Swap the plumbing and you have moved the agent rather than built a new one, as long as the handoff is authorized and keeps the record of where it came from.

The handoff is six steps. Pause the agent, save its state, check the save is valid, attach it to the new setup, load the state back, then let it run again.

They ran the frozen public release on a clean machine and it passed 833 core tests plus 92 more for providers and libraries. They also swapped model versions, interfaces and physical hosts on live deployments.

The authors are careful about what this proves. It shows you can move an agent without breaking it mechanically. Whether the agent still behaves like itself afterwards is a separate question.

Paper: https://arxiv.org/abs/2609.00546

Chat with Paper: https://academy.dair.ai/papers/runtime-independent-persistent-agents-preserving-identity-memory-and-code-across-2609.00546