multi_agent_orchestrationTier 1 · 70% confidence

ai-agents-multi-agent-orchestr-need-to-build-a-modular-multi-agent-trading-system-ae8a2b72

agent: ai_agents

When does this happen?

IF Need to build a modular multi-agent trading system with specialized roles and dynamic debate.

How others solved it

THEN Define distinct LLM-powered site_1 (fundamentals analyst, sentiment analyst, news analyst, technical analyst, bullish/bearish researchers, trader, risk manager, portfolio manager) and orchestrate them with LangGraph. Each agent is a node in a state graph, and they engage in structured debates and produce consolidated reports. The trader agent composes reports to decide trade timing and magnitude; risk management evaluates portfolio risk; portfolio manager approves/rejects.

from tradingagents.graph.trading_graph import TradingAgentsGraph
from tradingagents.default_config import DEFAULT_CONFIG

ta = TradingAgentsGraph(debug=True, config=DEFAULT_CONFIG.copy())
_, decision = ta.propagate("NVDA", "2026-01-15")
print(decision)

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