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Dev.to
Dev.to
7/5/2026
The original title is: "I Designed a RAG Variant for Multi-Agent Simulations. Here's the Design and the Honest Tradeoffs."

The original title is: "I Designed a RAG Variant for Multi-Agent Simulations. Here's the Design and the Honest Tradeoffs."

Original: I Designed a RAG Variant for Multi-Agent Simulations. Here's the Design and the Honest Tradeoffs.

Short summary

The author designed TCMF, a RAG retrieval system for multi-agent simulations combining episodic memory scoring (relevance, recency, importance) with causal graph analysis. It retrieves memories that caused current events, not just semantically similar ones. Includes Python code and architectural tradeoffs for building causality-aware systems.

  • •TCMF fuses episodic memory scoring with causal graph analysis to improve retrieval
  • •Understands root causality: what events triggered the current crisis, not just semantic matches
  • •Concrete Python implementation with NetworkX graphs and depth-weighted causal boosting

Generated with AI, which can make mistakes.

#ai-tools#ai-agents#research-breakthrough
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