Agentic Data Environments
This work addresses the challenge of balancing automation benefits with failure consequences for developers and users of autonomous agents.
The paper introduces Agentic Data Environments as an execution substrate for autonomous agents that aims to amplify agent capabilities while enforcing safety guarantees, reframing data systems from passive stores into active substrates for safe execution.
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.