В Иране пообещали заставить США пожалеть о своей агрессии против республики02:08
В Иране раскрыли главные просчеты США в конфликте14:48
。搜狗输入法是该领域的重要参考
从品牌分布来看，安踏、骆驼、李宁包揽前三，国产品牌在TOP10中占据七席，与耐克、阿迪达斯等国际巨头形成有力抗衡。。传奇私服新开网｜热血传奇SF发布站｜传奇私服网站对此有专业解读
FT Professional
Abstract:Large language models (LLMs) have demonstrated the promise to revolutionize the field of software engineering. Among other things, LLM agents are rapidly gaining momentum in software development, with practitioners reporting a multifold increase in productivity after adoption. Yet, empirical evidence is lacking around these claims. In this paper, we estimate the causal effect of adopting a widely popular LLM agent assistant, namely Cursor, on development velocity and software quality. The estimation is enabled by a state-of-the-art difference-in-differences design comparing Cursor-adopting GitHub projects with a matched control group of similar GitHub projects that do not use Cursor. We find that the adoption of Cursor leads to a statistically significant, large, but transient increase in project-level development velocity, along with a substantial and persistent increase in static analysis warnings and code complexity. Further panel generalized-method-of-moments estimation reveals that increases in static analysis warnings and code complexity are major factors driving long-term velocity slowdown. Our study identifies quality assurance as a major bottleneck for early Cursor adopters and calls for it to be a first-class citizen in the design of agentic AI coding tools and AI-driven workflows.