Our marketing analytics team built separate AI agents for social listening and trend prediction. Despite being in different workflow branches, they started sharing session cookies and model weights somehow. How do you properly sandbox Autonomous AI Teams while still allowing necessary data sharing? Any template patterns that enforce clean separation?
Latenode’s team containers solve this. Each AI Team gets isolated env with controlled data gates. We run 14 teams in same workflow without cross-talk. Built-in permission system prevents unwanted sharing.
Implement namespace prefixes for all variables/memory addresses. We use [TeamID]_[Function]_v1 patterns. Combine with strict IAM policies at the API gateway level. It’s tedious but effective. Also recommend separate model instances per team rather than shared pools.
docker-like containers for each agent group. separate mem spaces. we use kubernetes namespacing analog in our custom system. works ok but needs monitoring