Why it matters
Documents have careers: draft, review, publish, monitor, expire, archive. AI treats all text as equally believable unless lifecycle state says otherwise. Lifecycle management ensures bots stop citing promos after they end and never touch drafts meant for next quarter.
Ignoring lifecycle turns your index into a museum of outdated facts with modern confidence.
How it works
Encode states in metadata synced from CMS or enforced in the knowledge platform. Transitions trigger index updates, owner notifications, and regression tests.
Define retirement: archived docs remain for audit but leave live retrieval. Expired promos move to historical collections blocked for customer apps.
Example
Nintendo summer promo articles auto-expire in August. Lifecycle rules remove them from the chatbot collection but keep copies for marketing analytics. Support macros linked to those articles trigger review tickets. Customers asking about summer pricing get current standard plans, not expired deals.
Common mistakes
- 1Binary published/unpublished with no expired state
- 2Archival in CMS that does not propagate to vector indexes
- 3No owner notification on upcoming review dates
- 4Lifecycle rules that differ between help center and policy hub
Every AI deserves a source of truth.
Organize verified knowledge collections with ownership, review dates, and lifecycle controls.
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