In plain English
This page is part of the technical reference. It keeps the expert detail but starts with a plain-language summary for first-time readers.
- Why this matters: AI risk can come from the whole arrangement, not one obvious model.
- What to look for: data, memory, routes, adapters, tools, evaluators, updates, and rollback paths.
- Technical version below: the expert terminology remains available and is linked through the glossary.
Model Retirement Failure and Zombie Behavior
Direct answer
A model ecologyA changing AI system made from many connected parts, not just one model. Open glossary definition without retirement becomes a landfill of old behavior.
Retirement is not simply deleting a file. It is a lifecycle operation that removes or accounts for active artifacts, permissions, routes, memory, data, documentation, aliases, dependencies, and side effects.
Why retirement matters
Models drift. Data changes. regulations change. dependencies expire. safety evidence goes stale. old variants keep permissions. documentation points to outdated assumptions. a route or alias may still send traffic to an old behavior path.
If a model learns bad shortcuts, violates boundaries, loses provenanceA record of where a component or behavior came from. Open glossary definition, or performs worse under new evaluations, retirement should be a safety response.
Zombie behavior
Zombie behaviorOld behavior that was not actually gone. Open glossary definition is a behavior that should have been retired but remains active through another route: memory, synthetic data, descendant models, support macros, release aliases, evaluator preferences, old tools, or human workflows.
What to watch for
- deprecated model still reachable through alias;
- old adapterA small add-on that changes or specializes model behavior. Open glossary definition still stored in registry with valid signature;
- endpoint removed but permission tokens remain live;
- memory snapshotA saved state of what the AI system remembers. Open glossary definition predates a safety fix;
- synthetic data from retired behavior remains in training pool;
- no proof that downstream descendants were reviewed;
- retirement ticket closes before side effects are inventoried.
Retirement evidence packet
A real retirement packet should include retirement trigger, affected artifacts, traffic migration, memory cleanup, data quarantine, dependency cleanup, permission revocation, stakeholder notice, rollbackReturning a system to an earlier known state. Open glossary definition plan, archive hash, owner sign-off, and behavioral-extinction review.