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Long-Term Memory

Master how AI agents store and retrieve knowledge across sessions using persistent memory systems

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Beyond the Conversation: Persistent Memory

Imagine an agent that remembers you—not just for the duration of a chat, but across weeks, months, or even years. It recalls your preferences, past conversations, projects you've worked on together, and builds on that knowledge over time.

That's the power of long-term memory. Unlike short-term memory (context windows), which disappears when the session ends, long-term memory persists across interactions. It's stored externally—in databases, vector stores, or knowledge graphs—and retrieved when needed.

This module explores how agents store, organize, and retrieve knowledge that outlives any single conversation.

Interactive: Memory Type Comparison

⏰

Short-Term (Context Window)

Storage:In-memory, temporary buffer
Duration:Lasts only during the session
Capacity:Limited (2K-128K tokens)
Access:Immediate, no retrieval needed
Use Case:Current conversation context

Analogy: Like holding a thought in your head while having a conversation—it disappears when you move on.

Interactive: Retention Period Explorer

How long should an agent remember? Adjust the retention period to see different use cases.

1 hours
1h1 day1 week1 month1 year
⏱️

Minutes

Typical use: Current conversation

Memory Type
Short-Term (Context)
Storage Method
In-memory buffer
Example Use Case
Live chat support
Retrieval Cost
Free (in-context)

Why Long-Term Memory Matters

✅ Enables

  • • Personalization: Remember user preferences
  • • Learning: Build knowledge over time
  • • Continuity: Pick up where you left off
  • • Context: Reference past interactions

🔧 Requires

  • • Storage: Databases (SQL, vector, graph)
  • • Retrieval: Search/query mechanisms
  • • Organization: Structure and indexing
  • • Privacy: Security and data management

💡 Key Distinction

Short-term memory is like your computer's RAM—fast, immediate, but temporary. Long-term memory is like your hard drive—slower to access, but it persists. The best agent systems use both: recent context in RAM, historical knowledge on disk.