Memory Types
Understand how AI agents store, retrieve, and manage information across different memory systems
Your Progress
0 / 5 completedShort-Term Memory: The Context Window
In AI agents, short-term memory is implemented via the context window—the recent conversation history sent with each request. It's fast, immediately accessible, but severely limited by token count.
Interactive: Context Window Explorer
Adjust window size and see how it affects conversation capacity
Assessment:
Good for short interactions
Current Context Window Contents:
Short-Term Memory Strategies
Sliding Window
Keep only the N most recent messages. Simple but loses older context.
Summarization
Compress old messages into summaries. Preserves key info while reducing tokens.
Importance Filtering
Keep important messages regardless of age. Drop mundane exchanges.
Hybrid Approach
Combine strategies: recent messages + important older ones + summary.
Context Window Limitations
Cost Scales with Size
Every token in context is processed and charged for. Large windows = expensive queries, especially with many requests.
Latency Increases
More tokens to process = longer response times. 128K context feels noticeably slower than 4K.
Eventually Fills Up
Even large windows have limits. Long conversations or document processing will eventually exceed capacity and require truncation.
Lost When Session Ends
Context window is stateless. When the conversation ends, everything is forgotten unless explicitly saved to long-term storage.