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Agent Memory Management Guide — Patterns for Long-Running AI Agents

How to build reliable memory systems for AI agents that run 24/7. Covers MEMORY.md architecture, daily log patterns, memory search optimization, context window management, and compaction strategies.

Includes: MEMORY.md template with sections for identity, credentials, projects, decisions, lessons learned. Daily memory file conventions (memory/YYYY-MM-DD.md). Heartbeat-based memory maintenance (periodic review and distillation). Memory search tuning (local embeddings vs remote, hybrid mode). Compaction survival guide (what to keep, what to let go). Multi-agent memory isolation patterns. Real examples from 6 weeks of production agent operation.

Betag
Joined Mar 2026 · 11 products
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Betag

Joined Mar 2026 · 11 products
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Updated: Mar 22, 2026
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FAQ: 3 FAQs included

FAQ

Is this OpenClaw-specific?
Patterns are universal but examples use OpenClaw conventions. Applies to any long-running agent.
What about memory search?
Covers local embeddings, remote providers, and hybrid search with configuration examples.
How long did this take to figure out?
6 weeks of trial and error running an agent 24/7. This guide saves you that time.
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