Git4Data introduces a database-native version‑control layer that treats a database as a repository and each table as a versioned object, exposing Git‑style operations—snapshot/tag, branch, diff, and merge—through SQL extensions. Implemented in MatrixOne, it leverages immutable object storage and MVCC so that operation costs depend on the size of the change rather than the entire dataset. In agentic branching workloads, Git4Data outperforms DoltDB by up to an order of magnitude, demonstrating efficient versioning for AI agents.
By Hongshen Gou, Zuyu Zhang, Yuze Sun, Peng Xu, Feng Tian, Long Wang, Jianguo Wang
arXiv:2606. 01185v1 Announce Type: new Abstract: Coding agents are becoming users of data infrastructure, but their success depends not only on model quality: it also depends on the skills and environment files that teach agents how to use a system.
By Nicole Rose Schneider, Davide Ghilardi, Giacomo Piccinini, Jacopo Tagliabue
arXiv:2606. 01185v2 Announce Type: replace Abstract: Coding agents are becoming users of data infrastructure, but their success depends not only on model quality: it also depends on the skills and environment files that teach agents how to use a system.
By Nicole Rose Schneider, Davide Ghilardi, Giacomo Piccinini, Jacopo Tagliabue
arXiv:2608.29204v1 Announce Type: cross
Abstract: Generative AI-based software engineering agents are becoming routine contributors to real-world software projects. On GitHub, developers can assign t...
By Jonan Richards, Kosei Horikawa, Youmei Fan, Yutaro Kashiwa, Mairieli Wessel
AgileLog introduces a forkable shared log designed to support AI agents that interact with streaming data. The new abstraction provides forking primitives that allow agents to operate without causing performance interference or unsafe writes. Bolt is a system that implements AgileLog, employing techniques to keep forks inexpensive while ensuring logical and performance isolation.
By Shreesha G. Bhat, Tony Hong, Michael Noguera, Aishwarya Ganesan, Ramnatthan Alagappan
arXiv:2606. 14470v1 Announce Type: new Abstract: Large language model (LLM) reasoning is ephemeral: chains of thought vanish with the context window, pruned search branches leave no record, and memory buffers cannot be diffed, merged, or audited.
By Pavan C Shekar, Abhishek H S, Aswanth Krishnan
arXiv:2606. 28279v1 Announce Type: cross Abstract: We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution.
By Cunxi Yu, Chenhui Deng, Nathaniel Pinckney, Brucek Khailany
arXiv:2511.20109v2 Announce Type: replace
Abstract: Climate science demands automated workflows to transform comprehensive questions into data-driven statements across massive, heterogeneous datasets...
By Chenyue Li, Hyeonjae Kim, Wen Deng, Mengxi Jin, Wen Huang, Mengqian Lu, Binhang Yuan
arXiv:2607. 14390v1 Announce Type: cross Abstract: Coding agents now produce a growing share of a team's code, while the reasoning behind each change -- the alternatives weighed, the constraints discovered, the approaches rejected -- is trapped in assistant transcripts that vanish with the session.
By Frank Guo
arXiv:2606. 04755v1 Announce Type: cross Abstract: We present Archi, an open-source, end-to-end framework for scientific collaborations that combines the systematic ingestion and organization of heterogeneous data sources with the deployment of configurable, private, and extensible agents that retrieve and reason over them.
By Pietro Lugato, Luca Lavezzo, Jason Mohoney, Hasan Ozturk, Muhammad Hassan Ahmed, Juan Pablo Salas, Viphava Ohm, Krittin Phornsiricharoenphant, Gabriele Benelli, Mariarosaria D'Alfonso, Manasvita Joshi, Warren Nam, Aron Soha, Samantha Sunnarborg, Austin Swinney, Jack Tucker, Dmytro Kovalskyi, Tim Kraska, Christoph Paus
SpecMine is a large-scale corpus that documents Spec-Driven Development (SDD) artifacts in public GitHub repositories. It includes a broad census of 470,795 spec files from 73,030 repositories linked to 17 tools, a focused census of 98,574 Kiro layout files from 12,910 repositories, and a sweep of 5,992 pull requests across 581 repositories that modify specs. The dataset provides enriched metadata, full commit histories, parsed document structures, and over 2.4 million typed references connecting specs to code, sibling documents, PRs, branches, and issues.
By Shyam Agarwal, Anmol Singhal, Travis Breaux, Bogdan Vasilescu
Advanced agents are increasingly demonstrating the potential to operate as autonomous engineers, creating a growing demand for evaluation benchmarks that capture the complexity of real-world development. Such environments typically involve both complex code and large-scale data (i.