OpenClaw Memory Management Guide: Build a 3-Layer System That Actually Sticks

Most agent failures come from memory chaos, not model quality. The fix is structural: separate short-term state, daily logs, and long-term memory into clear layers.

Layer 1: Working Memory (Current Task State)

Keep only active context needed to complete the current objective. Avoid dragging entire chat history into every turn.

• What to store: objective, current blockers, next action
• When to update: after each meaningful step
• Retention: task lifetime only

Layer 2: Daily Memory (Execution Log)

Use date-based logs to capture decisions and outcomes. This creates a searchable audit trail without polluting your long-term memory.

• Context
• Decision + reason
• Artifact changed
• Next step

Layer 3: Long-Term Memory (Durable Signals)

Promote only stable patterns: user preferences, architecture choices, and validated workflows. Skip transient chatter.

Review Cadence

• Daily: append log entries
• Weekly: promote durable learnings
• Monthly: prune stale or conflicting memory items