| title | Agentic Transaction: Towards ACID-Compliant Agent Systems |
|---|---|
| authors | Zhaoyan Sun, Xiaoxiao Wang, Guoliang Li |
| date | 2026-08-14 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2608.13900 |
| affiliation | Tsinghua University |
| upvotes | 28 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf code |
| abstract | Large language model (LLM) agents are evolving from conversational assistants into autonomous systems that execute long-horizon tasks through reasoning, tool use, code generation, and workspace manipulation. As agents increasingly operate over persistent environments and multi-step workflows, they face challenges analogous to those addressed by transactional database systems: reliable execution, consistent outcomes, safe concurrency, and durable state management. We introduce the concept of an agentic transaction and propose an ACID-compliant agent system framework that reinterprets the classical ACID properties for agent execution through four semantic guarantees: Semantic Atomicity, Semantic Consistency, Semantic Isolation, and Semantic Durability. Together, these properties provide a principled foundation for building reliable agent systems despite model uncertainty and dynamic execution environments. To instantiate this framework, we develop an ACID-compliant data agent that realizes these guarantees through transactional exploration-execution-validation cycles, transactional skill hubs, confidence divergence-based validation, semantic dependency-aware isolation, and transaction-aware semantic state management. Experimental results on widely used benchmarks show that our system achieves a 10.6% improvement over state-of-the-art agents, including Claude Code. This work opens a broader research agenda on extending transactional principles and system architectures toward building trustworthy, scalable, and self-evolving AI agent systems. |
cite
@misc{sun2026agentic,
title={Agentic Transaction: Towards ACID-Compliant Agent Systems},
author={Zhaoyan Sun and Xiaoxiao Wang and Guoliang Li},
year={2026},
eprint={2608.13900},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2608.13900}
}