Definition
Designing AI agents so their reliability stays good over weeks and months of use, not just on day one.
The design discipline of monitoring and intervening on multi-mechanism agent aging across deployment, treating reliability as a lifespan property of the agent-plus-memory system rather than a model snapshot.
Also called: agent lifespan engineering