Glossary
Agent Memory Decay
The gradual degradation of an agent's retrieved or stored context — stale reads, outdated embeddings, compounding errors carried forward from earlier steps — that surfaces as silent quality drift rather than a hard failure or a triggered alert.
It rarely triggers an alert on its own. It surfaces indirectly, as rising refusals, longer latencies, or cost creep — which is what makes it easy to miss until it's already affecting users.
How do you catch agent memory decay before it affects users?
Since it rarely triggers a hard alert, teams typically watch for its downstream symptoms instead — rising refusal rates, longer latencies, or gradual cost creep — and treat a change in any of those as a signal to check whether stored context or retrieved embeddings have gone stale.
Where this comes up
AI Agent Failure Modes in Production
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