Foundation models are increasingly adapted after release through continual pretraining, in-struction tuning, alignment updates, retrieval refresh, model editing, test-time learning, and agentmemory updates. The central weakness in much of the evaluation culture is that adaptation successis often reported as new-task gain while the survival of old capabilities, calibration, safety behavior,cross-domain transfer, and rollback readiness remain secondary. This paper introduces the ContinualAdaptation Stability-Plasticity Contract (CASP), a release-gated model for auditing whether afoundation-model update is both plastic enough to learn and stable enough to preserve what shouldnot be lost. A candidate update is compiled into a contract object containing new-task gain, old-taskretention, drift, contamination risk, negative controls, transfer stability, repeated-update stability,and rollback status. The paper defines a stability-plasticity score, a critical missing-channel operator,and a release rule that blocks gain-only claims when retention, drift, provenance, or rollback evidenceis missing. A completed 3000-record diagnostic ledger is reported across ten adaptation domainsand eight update modes. In that ledger, only 5 records become release candidates, 554 becomehigh-value holds, and 2441 become critical holds. The leading missing channel is cross-domaintransfer, followed by old-task retention, negative controls, repeated-update stability, drift bounds,rollback protocols, and contamination audits. A 41-test Python verification suite checks the scorelaw, half-life computation, missing-channel gates, rollback-safe database behavior, timeout-safepolling, explicit network timeouts, slow-dependency mocking, serialization, and aggregate-ledgerconsistency. The contribution is a standalone scientific model: adaptation claims should not bereleased by improvement alone; they should carry evidence that the update has not silently brokenthe model it claims to improve
Tony Newton (Sun,) studied this question.