Maintenance and Updates › Maintenance and Updates

Your agent is deployed and running reliably. Users are interacting with it daily. The monitoring dashboard shows healthy metrics. Everything is working. But here's the thing: "working today" doesn't mean "working forever."

The world around your agent keeps changing. Language models get updated with new capabilities. APIs you depend on change their interfaces. New tools become available that could make your agent more useful. Users discover edge cases you never anticipated. Costs drift upward as usage grows. Security vulnerabilities are discovered in dependencies.

Maintenance is how you keep your agent working well despite these changes. Updates are how you make it better over time. Together, they transform your agent from a static artifact into a living system that evolves with its users' needs and the changing technology landscape.

In this chapter, we'll explore the ongoing work of maintaining an AI agent. You'll learn how to update your agent safely, manage costs, respond to feedback, and keep the system healthy over months and years. This is where deployment becomes operations, and where your agent grows from a promising prototype into a dependable tool.