How to Handle Long-Running SaaS API Tasks in AI Agent Workflows

You have built an AI agent that correctly identifies user intent, formats the required JSON arguments, and triggers a function call to external systems like Salesforce or Jira. In your local development environment, it reasons beautifully. It picks the right tool and chains steps together like a senior engineer. Then you deploy it to production and point it at a real customer’s data—a Salesforce export, a NetSuite saved search, or a 90,000-record HubSpot contact list. Within hours, the whole thing collapses.