agentdb-persistent-memory-patterns

Implement persistent memory patterns for AI agents - session memory, long-term storage, pattern learning, and context management.

When to Use

• Building stateful agents with memory
• Creating chat systems with context
• Implementing intelligent assistants
• Managing agent learning patterns

Quick Start

npm install agentdb-memory
npx ts-node setup-memory.ts

5-Phase Workflow

1. Design Memory Architecture (1-2 hrs) - Schema and storage layers
2. Implement Storage Layer (2-3 hrs) - Memory stores and persistence
3. Test Memory Operations (1-2 hrs) - Validation and benchmarking
4. Optimize Performance (1-2 hrs) - Caching and query optimization
5. Document Patterns (1 hr) - Usage docs and examples

Memory Types

• Episodic: Event memories
• Semantic: Knowledge facts
• Procedural: Learned skills
• Working: Active context

Success Metrics

• Memory persists across sessions
• Retrieval < 50ms (p95)
• Pattern recognition > 85% accuracy
• Context maintained accurately

Agents Used

• memory-coordinator: Memory architecture design
• swarm-memory-manager: Distributed memory management
• backend-dev: Storage implementation

Estimated Duration

6-8 hours for complete implementation