Agentic Data Environments
Abstract
Autonomous agents promise substantial gains in speed, scale, and labor efficiency, but their failures can impose abrupt and often irreversible costs. The central challenge for agentic automation is therefore to increase the benefits of automation while bounding the consequences of failure. While databases remain central to modern computing, agents operate over a broader data environment spanning files, APIs, applications, and system state. In this talk, I will outline early work on Agentic Data Environments -- the execution substrate in which agents operate -- that both amplify agent capabilities and enforce safety guarantees. This perspective reframes data systems from passive stores of state into active substrates for safe, reliable execution.
Cite
@article{arxiv.2607.07397,
title = {Agentic Data Environments},
author = {Elaine Ang and Chenxi Huang and Georgios Liargkovas and Jerry Liu and Jinhui Liu and Nikos Pagonas and Charlie Summers and Haonan Wang and Jiakai Xu and Tianle Zhou and Yusen Zhang and Zhou Yu and Zhuo Zhang and Tianyi Peng and Kostis Kaffes and Eugene Wu},
journal= {arXiv preprint arXiv:2607.07397},
year = {2026}
}