13-5: State Management & Memory Costs
Long-term memory persistence, Vector vs Graph DB architecture, and the cost of recalling agent state.
🎯 What You'll Learn
- ✓ Calculate Vector memory vs Graph memory Opex
- ✓ Model context window eviction strategies
- ✓ Optimize cross-session persistence
The Economics of Infinite Memory
For an agent to be truly useful, it needs episodic memory—it must remember what the user told it three weeks ago. Storing this memory requires sophisticated state management.
You cannot simply shove the entire 3-week conversation history into the LLM context window—that would cost $20 per query. You must use RAG, Semantic Routing, or Knowledge Graphs to recall only the relevant memories.
Knowledge Graphs (like Neo4j) map entity relationships flawlessly but carry high setup costs, whereas Vector Databases are fast but struggle with complex logical reasoning.
The accuracy of the agent fetching the correct historical context.
The cloud infra cost of maintaining active agent memory graphs.
Implement a memory eviction policy for your agent platform.
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Module Syllabus
Lesson 1: The Economics of Infinite Memory
For an agent to be truly useful, it needs episodic memory—it must remember what the user told it three weeks ago. Storing this memory requires sophisticated state management.You cannot simply shove the entire 3-week conversation history into the LLM context window—that would cost $20 per query. You must use RAG, Semantic Routing, or Knowledge Graphs to recall only the relevant memories.Knowledge Graphs (like Neo4j) map entity relationships flawlessly but carry high setup costs, whereas Vector Databases are fast but struggle with complex logical reasoning.
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