5 citations · 6 across the 5 of their papers we have counts for
4 papers · 1 filter
A Few Pages of Markdown: Committed AI Configuration and Lower Quality Cost after Coding-Agent Adoption
Yegor Denisov-Blanch, Shyam Agarwal, Pavel Azaletskiy +5
Coding agents increase development velocity but also technical debt. Prior work reports only average effects across adopters, hiding wide differences between teams. We introduce RA…
AI Writes Faster Than Humans Can Review: A Longitudinal Study of an Enterprise 2x Mandate
Hao He, Shyam Agarwal, Yegor Denisov-Blanch +3
Enterprises increasingly mandate the use of AI coding tools and announce ambitious productivity targets, yet there is little longitudinal evidence on whether such productivity targ…
AI IDEs or Autonomous Agents? Measuring the Impact of Coding Agents on Software Development
Shyam Agarwal, Hao He, Bogdan Vasilescu
Large language model (LLM) based coding agents increasingly act as autonomous contributors that generate and merge pull requests, yet their real-world effects on software projects…
Speed at the Cost of Quality: How Cursor AI Increases Short-Term Velocity and Long-Term Complexity in Open-Source Projects
Hao He, Courtney Miller, Shyam Agarwal +2
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 softwa…