OAuth Token Vault Patterns for AI Agents

Your AI agent just got OAuth tokens for a user's Google Calendar. Now what? If the answer is "store them in a variable and use them until they expire," you have a security problem. I have built production AI systems that handle user tokens for API calls, and the number of agents holding raw access tokens in memory with zero protection is genuinely alarming. Let's fix that. Here are four battle-tested patterns for secure token management in AI agent systems. The Problem: Agents Are Terrible Token Custodians Most agent frameworks treat OAuth tokens like any other string. Fetch a token, stuff it in the agent's context or a plain database column, and make API calls. This creates three real problems: Token leakage through logs and traces. Agents produce verbose logs. Raw tokens end up in debug output, error messages, and observability platforms. Refresh race conditions. Two agent threads hit a token expiry at the same time. Both try to refresh. One gets a new token, the other gets an invali