In this extended abstract, we propose a novel research topic in the field of agentic AI, which we refer to as self-coding information systems. These systems will be able to dynamically adapt their structure or behavior by evaluating potential adaptation decisions, generate source code, test, and (re)deploy their source code autonomously, at runtime, reducing the time to market of new features. Here we motivate the topic, provide a formal definition of self-coding information systems, discuss some expected impacts of the new technology, and indicate potential research directions.

翻译：在这篇扩展摘要中，我们提出了智能体人工智能领域的一个新颖研究方向，即自编码信息系统。这类系统能够通过评估潜在的适应性决策，在运行时动态调整其结构或行为，自主生成源代码、进行测试并（重新）部署其源代码，从而缩短新功能的上线周期。本文阐述了该主题的研究动机，给出了自编码信息系统的形式化定义，探讨了这项新技术可能带来的影响，并指出了潜在的研究方向。