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Research
Why Memory-Equipped AI Agents Are Outperforming Traditional Systems in Commodity Trading
New research shows agentic AI with persistent memory consistently outperforms rule-based trading in commodities — but the real edge isn't the model. It's the memory architecture.
References
- [1] Agentic AI in Commodity Trading: A Comparative Simulation Study https://thesai.org/Downloads/Volume16No11/Paper_2-Agentic_AI...
- [2] AI Agents for Commodity Trading - Whitepaper https://revenue.ai/wp-content/uploads/2025/05/AI-Agents-for-...
- [3] The Brains Behind the Bots: A Comprehensive Guide to AI Agent Memory in 2026 https://medium.com/aimonks/the-brains-behind-the-bots-a-comp...
- [4] A 2026 Memory Stack for Enterprise Agents https://alok-mishra.com/2026/01/07/a-2026-memory-stack-for-e...
- [5] How to Build Memory-Driven AI Agents with Short-Term, Long-Term, and Episodic Memory https://www.marktechpost.com/2026/02/01/how-to-build-memory-...
- [6] Agentic Trading: Where Ethics, Risk, and Alpha Collide https://kx.com/blog/agentic-trading-where-ethics-risk-and-al...
- [7] AI Agents in Automated Trading (Q3 2025 Report) https://www.multialpha.com/research/38/