AI Agents Inventory and Attributes - Lifecycle and Status attributes for the AI Agents Inventory
AI Agents Inventory and Attributes
Chapter 13. Lifecycle and Status attributes for the AI Agents Inventory
Executive Summary: Chapter Overview
IF4ITThe Bottom Line
Core Concepts
| Concept | Definition & Strategic Role |
|---|---|
| Lifecycle Status | The governed state of the agent — Proposed, Active, Under Review, Deprecated, Retired, Archived. |
| Decommission plan | The predefined steps to retire an agent and revoke its identity and access, so retirement is clean. |
Quick Q&A
Question: Why does an agent need an explicit decommission plan?
Read More Below
Lifecycle and status attributes govern each agent’s state over time, from proposal through active operation to retirement and archival.
| Attribute Name | Maturity | Description and Notes |
|---|---|---|
| Lifecycle Status | Crawl | Description — The agent’s current governed lifecycle state. Benefit(s) — Distinguishes active agents from proposed, deprecated, or retired ones for governance and reporting. Source — Manual. Examples — Proposed; Active; Under Review; Deprecated; Retired; Archived |
| Deployment Date | Walk | Description — The date the agent was first placed into production. Benefit(s) — Anchors age, review cadence, and lifecycle analysis. Source — Manual. |
| Last Modified Date | Walk | Description — The date the agent’s configuration (instructions, tools, guardrails, or model) was last changed. Benefit(s) — Flags recent change that may warrant re-evaluation or re-attestation. Source — Derived. Notes — Often derived from the source platform. |
| Decommission Plan | Walk | Description — The predefined steps to retire the agent, including revoking its non-human identity, credentials, and access. Benefit(s) — Prevents retired agents from lingering with live access — a common source of shadow risk. Source — Manual. |
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