Memory Types
Understand how AI agents store, retrieve, and manage information across different memory systems
Your Progress
0 / 5 completedWhy Memory Matters for AI Agents
Without memory, an AI agent starts every interaction from scratch—like having amnesia. It can't remember past conversations, learn from experience, or maintain context across tasks. Memory transforms agents from stateless responders into intelligent, adaptive systems that improve over time.
Interactive: Memory Systems Comparison
Human Memory Architecture
Humans use multiple specialized memory systems that work together seamlessly. Each type handles different kinds of information with varying retention periods.
Temporary storage for active tasks. Holds 7±2 items for seconds to minutes.
Personal experiences with context. "I remember when..."
Facts and concepts without personal context. General knowledge.
Skills and habits. "How to" knowledge that becomes automatic.
Interactive: Working Memory Capacity
The "magic number" is 7±2 items. Adjust to see how capacity affects performance.
Impact:
Optimal range - balances context retention with processing efficiency.
Current Working Memory Contents:
The Agent Memory Challenge
Unlike humans who naturally balance different memory types, agents must explicitly design their memory architecture. Key challenges:
Retention vs Retrieval
Storing everything is easy. Retrieving the right information at the right time is hard.
Cost vs Context
More context = better responses but higher token costs and slower processing. Must optimize the tradeoff.
Relevance Filtering
Not all past information is relevant to the current task. Agents need smart retrieval strategies to avoid information overload.