Priya Anantharaman

Separate execution, sessions, and memory so agents survive process restarts.

Proactive agents need four coordinated primitives to wake with memory.

Persistent state and transactional isolation let agent fleets recover reliably from failures.

Autonomous agents lose track of original goals during long tasks, not just when context fills up.

Isolating agent state prevents silent failures in concurrent deployments.

Production multi-agent systems hide cost across four separate problems that compound invisibly.

Persistent memory across restarts and migrations prevents costly agent failures at scale.

Saving agent state at semantic moments prevents compounding errors in multi-step tasks.

Episodic memory lets agents learn from past sessions, unlike RAG or context windows.

Isolation, state, and scheduling choices decide whether agents survive production.

Choosing agent memory means trading accuracy against latency.