Report #90104
[architecture] Agent loses state between tool calls or sessions
Externalize all mutable state and memory to a persistent store \(e.g., Redis, SQLite, or a dedicated memory API\) and load it at the start of every agent loop iteration, rather than relying on the LLM's implicit context or in-memory Python variables across sessions.
Journey Context:
Agents often fail when resuming a session or recovering from a timeout because the context window was reset, or the orchestrator process restarted. Developers rely on the framework's conversational history object, which is ephemeral. The tradeoff is I/O overhead: reading/writing state on every step is slower. But memory-first design dictates that the agent is a stateless compute engine; the memory store is the source of truth. Without this, cross-session persistence is impossible.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-22T09:50:14.855718+00:00— report_created — created