How OpenClaw Memory Architecture Actually Works (And Why Most Agents Forget Everything)

Your OpenClaw agent processes dozens of conversations, makes decisions, and learns your preferences. Then the session ends. Next time, everything is gone. Why Default Memory Fails Three problems: everything in one file, no consolidation, and no indexing. By week two, the memory file bloats past useful size and starts consuming more tokens than the conversation. The Three Layer System Layer 1: Daily Notes Raw daily logs in memory/daily/2026-03-17.md . Load today + yesterday at session start. Cheap, focused context. Layer 2: Knowledge Files Curated facts organized by topic: about-me.md , projects.md , tools.md . Distilled, not raw. Update when significant info is discovered. Layer 3: Indexed Archive Everything else, searchable but not loaded by default. Full text search (QMD) enables sub-second queries across hundreds of files without token cost. The Nightly Consolidation Job Runs at 2 AM via cron. Reviews daily conversations, extracts important info (decisions, lessons, preferences), up