Closed-Loop Learning
OpenSRE learns across sessions through long-term memory. When a conversation surfaces a durable fact — a root cause worth remembering, a known-flaky service, a naming convention, a preference — the agent stores it as a local memory file, and the memory index grounds every future conversation. There is nothing to configure: memories accrue as you work. Review what the agent has learned with/memory, inspect one entry with /memory show <name>, and correct course by deleting stale entries with /memory forget <name> or by simply telling the agent the updated fact.
See Long-Term Memory for storage locations, gateway scoping, and
how to turn memory off.