Algorithmic deprecation hazard
The reports emphasize a difficult truth: adaptive systems must forget, prune, merge, and retire components to remain efficient. But deprecation is also a safety boundary.
The efficiency problem
A system that never retires anything accumulates stale memory, redundant skills, obsolete policies, overlapping adapters, and confusing retrieval targets. Performance can degrade because the system has too many near-duplicate or contradictory options.
The assurance problem
The same deprecation mechanism can remove the structures that made the system safe, inspectable, reversible, or accountable.
| Deprecation action | Intended benefit | Assurance hazard |
|---|---|---|
| prune weights | reduce cost | remove safety-relevant structure |
| merge memories | reduce retrieval noise | blur origin and consent boundaries |
| retire adapter | simplify stack | leave descendant or synthetic residue |
| compress model | reduce memory | change refusal or calibration behavior |
| remove tests | speed release | create yardstick drift |
| collapse routes | reduce latency | change policy boundary |
Review rule
Every deprecation should produce a component retirement record. The record should state what was removed, what evidence depended on it, which descendants remain, which memory snapshots refer to it, and what rollback requires.
No-op as a control
Sometimes the safest action is not to add a new component, not to merge a component, and not to remove a component until the extinction and rollback implications are understood.