We look at TradingAgents, a popular open-source GitHub project that simulates a trading firm using a team of AI agents.
Instead of one AI model making a decision, this uses multiple specialized AI agents that analyze a stock from different angles like fundamentals, sentiment, technical analysis, bullish vs bearish research. They then debate before producing a final simulated trade decision.
🔗 Relevant Links
TradingAgents - https://tradingagents-ai.github.io/
GitHub Repo - https://github.com/TauricResearch/Tra...
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📌 Chapters:
0:00 AI agents debate stocks (TradingAgents intro)
0:36 What is TradingAgents? Multi-agent trading framework
1:25 Install + setup (Python 3.13, conda, API keys)
1:52 CLI demo: run a ticker + date + LLM
2:57 Python: customize config + run the graph
3:39 Pros: modular agents, learning, backtesting, open-source
4:09 Cons: token costs, rate limits, inconsistent outputs
4:33 What’s next: why multi-agent AI matters for devs
