AI编程工程师需像人类一样可靠，才能真正替代开发者。
Agentic AI Software Engineers: Programming with Trust
- 用LLM代理结合分析工具提升代码可信度
- 未来编程重心将从写代码转向验证代码信任度
- 适合关注AI工程化落地的开发者与研究者
大型语言模型（LLMs）在生成代码片段方面表现出惊人能力，有望通过人工智能（AI）自动化软件工程的大部分流程。我们认为，成功部署AI软件工程师需要达到甚至超过人类驱动软件工程实践所建立的信任水平。近期向LLM代理的趋势为整合LLM生成新代码的能力与分析工具增强代码可信度的能力提供了路径。本文探讨了LLM代理未来是否可能主导软件工程工作流，以及编程的焦点是否会从大规模编程转向以信任为核心的编程。
原文摘要 · Abstract (English)
Large Language Models (LLMs) have shown surprising proficiency in generating code snippets, promising to automate large parts of software engineering via artificial intelligence (AI). We argue that successfully deploying AI software engineers requires a level of trust equal to or even greater than the trust established by human-driven software engineering practices. The recent trend toward LLM agents offers a path toward integrating the power of LLMs to create new code with the power of analysis tools to increase trust in the code. This opinion piece comments on whether LLM agents could dominate software engineering workflows in the future and whether the focus of programming will shift from programming at scale to programming with trust.
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