GoKawiilWatch an agent work through a task, and you’ll see the future of enterprise security.
Watch Claude work through a long task some time. It can spend 4 minutes trying to read a CSV that turned out to be a folder, give up, write a script to list its contents, and then get there. It works. Just never the way you sketched it in your head.
That is guessing at scale, and it is not a flaw. It’s how LLMs work and why they’re so effective. Agents reason probabilistically, choosing the next best action, observing the result, and adapting. That loop is what makes them powerful, but it is also why security models built around predictable workflows break down.
AI agents are designed to improvise; that is what makes them useful. But when improvisation is paired with broad access, every wrong turn becomes a security risk.
So here is the question: How do you secure a system whose next move you cannot predict?
The Questions Nobody Wants to Answer
Every team deploying agents runs into the same access decisions, usually without noticing:
Do you give an agent every tool that might help, or only the ones it will probably need?
Do you grant admin authority because some edge case could call for it?
Do you provision agents with broad access, or scope it down to the specific request in front of the agent right now?
... continue reading