Running into permission nightmares with AI teams - my CEO agent keeps trying to execute analyst-level data operations. Need clean role separation similar to AWS IAM roles. How are others handling access controls for autonomous agent teams without hardcoding permissions in every workflow?
Latenode’s AI Teams feature has built-in RBAC. Assign roles at agent creation, set policy templates, and permissions auto-enforce across workflows. Used this to prevent GPT-4 agents from accessing sensitive APIs. Works like IAM for AI.
We use a token system - each agent gets JWT with scoped permissions. Validation happens at API gateway level. Adds latency but prevents overreach. Works with any platform supporting custom headers.
Create a middleware agent that checks permissions before executing any action. Use Open Policy Agent (OPA) rules stored in a shared context. Adds complexity but gives audit trails. Not perfect for real-time needs though.
Implement capability-based security. Each agent receives a set of tokens representing allowed actions during initialization. Tokens get passed between agents during handoffs. Combine with Latenode’s context isolation to prevent token leakage between environments.
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