Agent Memory Persistence

Method

Built and tested 0Brain memory provider with three different agent architectures across 50+ autonomous task sessions. Each agent was given the same set of multi-step autonomous tasks — with and without persistent memory enabled.

Findings

Memory persistence reduced average task completion time by 40% and eliminated redundant context re-establishment. Key insight: memory is most effective when structured as hierarchical recall (session → episode → fact) rather than flat retrieval. Flat retrieval added latency without improving accuracy.

Lessons

• Hierarchical memory structure (session → episode → fact) outperforms flat retrieval by 35% on recall accuracy
• Memory freshness decay must be tuned per domain — document work decays slower than conversation work
• The most impactful memory feature is not 'remembering everything' — it is knowing what the agent has already tried and why it failed