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What are common mistakes to avoid with Multi-Agent Systems

Intermediate

Answer

A common mistake with Multi-Agent Systems is applying it without fully understanding the underlying data or problem, which often leads to weak or misleading results. Skipping proper testing before relying on it in a real project is another frequent error.
Real-world example A multi agent system might use one agent to research information and another agent to write a final report based on that research.

Common follow-ups: What is AI Automation & Agents, How is Multi-Agent Systems evaluated in practice, What tools are commonly used for Multi-Agent Systems