What is an Agent Lifecycle?
The agent lifecycle encompasses all phases of an AI agent's operational existence — from provisioning and configuration through active operation, monitoring, updating, and eventual decommissioning — including associated wallet management at each stage.
WHY IT MATTERS
Like any production system, AI agents need lifecycle management. Creation isn't just deploying code — it's provisioning wallets, setting spending policies, configuring tools, and establishing monitoring. Decommissioning isn't just stopping — it's draining wallets, revoking approvals, and archiving audit logs.
The lifecycle phases include: provisioning (create wallet, set policies, fund initial balance), testing (sandbox evaluation), deployment (go live with monitoring), operation (ongoing monitoring, policy adjustments), updating (model changes, policy updates), and decommissioning (drain funds, revoke keys, archive logs).
Financial lifecycle management is particularly important. Forgotten agent wallets with remaining balances are a security risk. Stale approvals on decommissioned wallets are attack vectors. Clean lifecycle management prevents these issues.
HOW POLICYLAYER USES THIS
PolicyLayer manages spending policies throughout the agent lifecycle — from initial configuration through operational adjustments to final decommissioning. Policies are version-controlled and auditable across the full lifecycle.