agentdb-persistent-memory-patterns

skill_id	when-implementing-persistent-memory-use-agentdb-memory
name	agentdb-persistent-memory-patterns
description	Implement persistent memory patterns for AI agents using AgentDB - session memory, long-term storage, pattern learning, and context management for stateful agents, chat systems, and intelligent assistants
version	1.0.0
category	agentdb
subcategory	memory-management
trigger_pattern	when-implementing-persistent-memory
agents	["memory-coordinator","swarm-memory-manager","backend-dev"]
complexity	intermediate
estimated_duration	6-8 hours
prerequisites	["AgentDB basics","Memory management concepts","Database schema design"]
outputs	["Persistent memory architecture","Session and long-term storage","Pattern learning system","Context management APIs"]
validation_criteria	["Memory persists across sessions","Fast retrieval (< 50ms)","Pattern recognition working","Context maintained accurately"]
evidence_based_techniques	["Self-consistency validation","Chain-of-verification","Multi-agent consensus"]
metadata	{"author":"claude-flow","created":"2025-10-30T00:00:00.000Z","tags":["agentdb","memory","persistence","context-management"]}

AgentDB Persistent Memory Patterns

Overview

Implement persistent memory patterns for AI agents using AgentDB - session memory, long-term storage, pattern learning, and context management for stateful agents, chat systems, and intelligent assistants.

SOP Framework: 5-Phase Memory Implementation

Phase 1: Design Memory Architecture (1-2 hours)

• Define memory schemas (episodic, semantic, procedural)
• Plan storage layers (short-term, working, long-term)
• Design retrieval mechanisms
• Configure persistence strategies

Phase 2: Implement Storage Layer (2-3 hours)

• Create memory stores in AgentDB
• Implement session management
• Build long-term memory persistence
• Setup memory indexing

Phase 3: Test Memory Operations (1-2 hours)

• Validate store/retrieve operations
• Test memory consolidation
• Verify pattern recognition
• Benchmark performance

Phase 4: Optimize Performance (1-2 hours)

• Implement caching layers
• Optimize retrieval queries
• Add memory compression
• Performance tuning

Phase 5: Document Patterns (1 hour)

• Create usage documentation
• Document memory patterns
• Write integration examples
• Generate API documentation

Quick Start

import { AgentDB, MemoryManager } from 'agentdb-memory';

// Initialize memory system
const memoryDB = new AgentDB({
  name: 'agent-memory',
  dimensions: 768,
  memory: {
    sessionTTL: 3600,
    consolidationInterval: 300,
    maxSessionSize: 1000
  }
});

const memoryManager = new ({
  : memoryDB,
  : [, , ]
});


 memoryManager.({
  : ,
  : ,
  : { : , : .() }
});


 memories =  memoryManager.({
  : ,
  : ,
  : 
});