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Building a RAG-Powered Self-Improving Trading Department with LangGraph
Imagine walking into a trading floor that runs itself. Analysts don’t sleep, they never get tired, and they learn from their mistakes. Sounds sci-fi? Not anymore. In this post, we’ll build a RAG-powered, self-improving AI trading department using: gemini-2.0-flash for intelligent reasoning in our Agents LangGraph for orchestrating multi-agent workflows RAG (Retrieval-Augmented Generation) for continuous self-refinement It’s fun, modular, and actually gets smarter with each trading day.
Imagine walking into a trading floor that runs itself. Analysts don’t sleep, they never get tired, and they learn from their mistakes. Sounds sci-fi? Not anymore.
In this post, we’ll build a RAG-powered, self-improving AI trading department using:
- gemini-2.0-flash for intelligent reasoning in our Agents
- LangGraph for orchestrating multi-agent workflows
- RAG (Retrieval-Augmented Generation) for continuous self-refinement
It’s fun, modular, and actually gets smarter with each trading day.
