arXiv:2607. 08319v1 Announce Type: cross Abstract: We present GitLake, a Git-for-data design for an agent-first lakehouse.
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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.
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.
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.
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...
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.
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.