Agent Architecture for Persistence
The architecture allows AI agents to persist across model and infrastructure changes, potentially reducing development costs for companies in ASEAN.
The paper proposes splitting agents into persistent identity and replaceable plumbing components.
The architecture enables agents to outlive their original model, harness, or host through a six-step handoff process.
Authors tested the frozen public release on a clean machine, passing 833 core tests plus 92 provider and library tests.
They successfully swapped model versions, interfaces and physical hosts on live deployments.
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: arxiv.org/abs/2609.00546 Chat with Paper: academy.dair.ai/papers/runtime…📊 11 ⚡
This report is categorized under AITOP's "Papers" desk. Key entities and technical topics under continuous tracking include agent architecture, persistent agents, model migration, arxiv:2609.00546.
Source attribution: curated from elvis (@omarsar0).