AI Memory Patterns

Production patterns for building AI agent memory systems, distilled from operating a real multi-tenant system (154K+ observations, 3-node cluster) that competes with commercial offerings like Mem0 and Zep - architectural patterns and lessons, not a tutorial.

View source on GitHub

Key takeaways

• 01

  Patterns come from production scale, not toy demos

• 02

  Write/read/compress/update form the core memory pipeline

• 03

  Multi-tenancy forces clean memory isolation design

Flows built on this research

Memory & Context

Add File-Based Persistent Memory

Give your agent durable memory with plain files - the radical-minimalism approach production practitioners keep converging on.

4 steps · 45-75 minutes

Memory & Context

Memory Write Policies

Decide what gets remembered: write gates, provenance, confidence, and validation - because memory quality is set at write time.

4 steps · 60-90 minutes