What does it mean that agents have a lifecycle from creation to retirement?

Every agent is created, deployed, maintained, and eventually retired.

Example: You build a morning review agent — a daily protocol that scans your task list, checks calendar conflicts, and surfaces your top three priorities before you open email. For six months it works flawlessly. Then you change roles, your calendar tool changes, and the agent starts producing irrelevant output. You don't have a broken agent. You have an agent that has reached the maintenance-or-retire decision point in its lifecycle. Recognizing this is a lifecycle event — not a personal failure — lets you respond with precision: update the inputs, redesign the protocol, or retire it cleanly and build its successor.

Try this: Pick one cognitive agent you currently run — a decision protocol, a review habit, a planning routine, or a journaling practice. Map it to the four lifecycle stages: (1) When and why did you create it? (2) When did you actually deploy it into daily use? (3) What maintenance have you done — or failed to do? (4) Is it approaching retirement, and how would you know? Write your answers down. Most people discover that their agents are running on autopilot with zero maintenance — which means they are either decaying quietly or already functionally dead.