这篇论文搞了个DIA系统，用三个自主编码智能体自动处理企业数据查询，在7个SQL基准上全自主跑赢了所有已知最佳结果。
Data Intelligence Agents (DIA) 系统包含三个自主编码智能体：Data Interpreter、Schema Creator 和 Query Generator。该系统将自主编码智能体(ACA)作为第一类抽象，通过生成、执行、验证和修复具体构件，并利用共享记忆重用经验。DIA 已在企业客户的生产环境中部署。研究者对 Query Generator 进行了深入评估，在涵盖4个任务类别和4种方言的7个SQL基准上，其全自主模式匹配或超越了所有7个基准的最佳公开结果。
Data Intelligence Agents: Interpreting, Modeling, and Querying Enterprise Data via Autonomous Coding Agents
Production data integration is bottlenecked by repeated, lossy handoffs between data owners, engineers, and analysts who must collaboratively discover, structure, and query enterprise data. We present Data Intelligence Agents (DIA), a system of three agents (Data Interpreter, Schema Creator, and Query Generator) that compresses this workflow by treating autonomous coding agents (ACAs) as a first-class abstraction: rather than emitting text, the agents generate, execute, validate, and repair concrete artifacts, draw on a shared memory for experience reuse, and surface each for review by domain experts. DIA is deployed in production for enterprise customers. We study the Query Generator in depth and evaluate it in fully autonomous mode across seven SQL benchmarks spanning four task categories and four dialects. It matches or surpasses the best published results on all seven, demonstrating that an architecture grounded in execution, built on ACAs and a shared memory, generalizes across the data intelligence workload with adaptation confined to natural-language instructions.