Agent Credential Management: Two-Tier Service Accounts for Secure AI Agent Workflows

I spent three days trying to get a multi-agent system to talk to a Kubernetes API endpoint. Every time I used the default service account, the agent would hit a 403 and lock out. I was using the right permissions, the right roles, the right RBAC rules. It wasn’t until I implemented a two-tier service account system that the agents finally stopped throwing errors. It’s not just about having the right permissions , it’s about structuring them in a way that isolates the agent’s access and limits its blast radius. If you're running AI agents in Kubernetes, especially ones that interact with external systems or sensitive data, this is a pattern you should consider. This isn't just about security , it's about making sure your agents fail safely and don't accidentally break your entire infrastructure if they're compromised. I first tried using the default service account for all my agents. It worked fine for a while, but as I scaled out to more agents and more workflows, I started seeing odd