AI agents are fun until they start touching real data

Reddit r/AI_Agents News

Summary

The article discusses the governance challenges that arise when AI agents interact with real company data and tools, highlighting the need for policy enforcement and audit trails, and mentions Trust3 AI as a potential solution.

We’ve been experimenting with more AI agents internally and the weird part is the hard problem stopped being the AI itself pretty quickly. The moment agents started interacting with multiple tools and pulling actual company data, we realized we didn’t really have a clean way to control what they should access or trace what they actually did afterward. Logs help a bit, but once workflows get bigger it starts feeling pretty messy. I ended up going down a rabbit hole looking at governance tools and came across Trust3 AI. What caught my attention was enforcing policies directly inside the workflows themselves and having audit trails tied to agent activity instead of trying to piece everything together later. Are people already solving this somehow, or is everyone still kind of improvising as they scale? At what point did governance become something you actually had to think about seriously?
Original Article

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