State, Memory, and Replay as an Audit Contract
Learn how to design agent state and memory systems that enable reliable audit trails and replay capabilities, ensuring privacy, multitenant safety, and compliance. This lesson covers ephemeral and durable state handling, execution logs, and replay policies needed for robust AI governance and investigative traceability.
The orchestration pattern decides where planning happens and where tools get called. It says nothing about what has to survive after each step, or how anyone would prove later what actually happened. If an agent’s tool calls and decision trace can’t be replayed, no one can investigate an incident or prove anything about it. State design is a control surface. It determines auditability, privacy exposure, and whether a multi-tenant system can operate safely across cases and tenants with optional action initiation under oversight.
Agent state categories and explicit boundaries
Ephemeral working memory is the short-lived scratch space used to complete the current step: intermediate summaries, chain-of-thought-like reasoning, temporary tool outputs that don’t need to survive a retry. Keep this state inside the execution boundary and make it non-durable by default. Durability here only raises privacy exposure and widens the blast radius of a mistake.
Durable conversation or session state is the minimum information required to continue a session or resume a workflow after a failure: a stable session identifier, the latest user-visible messages, pointers to retrieved evidence. Use it to support continuity and recovery, not to accumulate everything the agent ever saw. Bound it explicitly to what reliability and audit actually require.
Long-term user preferences are durable settings that stay stable across sessions: preferred citation format, notification channel, a standing choice to require human approval for certain actions. Don’t let these substitute for retaining prior case details. Keep them separate ...