The paper introduces LibraryDesignBench, a benchmark that tests how well agents can design reusable libraries from specifications without prescribed designs. It evaluates libraries by measuring the correctness and simplicity of programs written by three different user agents across 242 programming problems in four languages. Findings show that while agents often replicate human-designed abstractions, downstream agents still tend to reimplement library features due to rigidity or usability issues, and that providing more prescriptive guidance improves reuse and program simplicity.
By Gabriel Orlanski, Alex L. Zhang, Avi Trost, Vincent Sunn Chen, Frederic Sala, Aws Albarghouthi, Ludwig Schmidt
arXiv:2607. 13285v1 Announce Type: new Abstract: The capability of a modern AI agent depends not only on its foundation model but also on its harness, which constructs prompts, manages state, invokes tools, and coordinates execution.
By Ruhan Wang, Yucheng Shi, Zongxia Li, Zhongzhi Li, Yue Yu, Junyao Yang, Kishan Panaganti, Haitao Mi, Dongruo Zhou, Leoweiliang
arXiv:2607. 21217v1 Announce Type: new Abstract: The recent emergence of vibe-coding workflows is changing what coding agents are expected to do.
By Zhongyuan Peng, Dan Huang, Chuyu Zhang, Caijun Xu, Changyi Xiao, Shibo Hong, David Lo, Lin Qiu, Xuezhi Cao, Jiyuan He, Yixin Cao
arXiv:2606. 05608v2 Announce Type: replace-cross Abstract: For over half a century, software engineering has operated on a foundational premise: human engineers decompose problems, encode decision logic into static code, and manually adapt that code as requirements evolve.
By Zhenfeng Cao
arXiv:2604. 14228v2 Announce Type: replace-cross Abstract: Claude Code is an agentic coding tool that can run shell commands, edit files, and call external services on behalf of the user.
By Jiacheng Liu, Xiaohan Zhao, Xinyi Shang, Zhiqiang Shen
The paper introduces Spec-Driven Agentic Development (SDAD), a framework that leverages large language models to ingest extensive functional requirement documents and repository context in a single workflow, turning specification quality into the engine for autonomous software delivery. SDAD blends disciplined upfront formalisation with rapid implementation, encompassing intent capture, machine‑readable specifications, agentic synthesis, and multi‑agent verification with human sign‑off. It positions AI‑code as a fourth production paradigm, compares it to traditional Waterfall and Agile approaches, and extends the model to team role evolution, quantitative governance metrics, and a staged migration blueprint for practical adoption.
By Vu Hung Nguyen, Thanh Nguyen