Dev Tools · 2h ago
When One AI Agent Fails, Split the Work: Multi-Agent Systems in Production
A team built a multi-agent system after a single agent hallucinated 15% of the time on document validation. They now split complex tasks across specialized agents, each with one job, using Celery for orchestration. The approach handles context limits and improves reliability by treating agent handoffs as a sequence.
Meridian48 take
The article offers a pragmatic, anti-hype take on multi-agent architectures, but the pattern described is essentially a microservices approach for LLMs—useful, but not novel.
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Multi-Agent Systems in Production: When One Agent Isn't Enough and How We Coordinate Them →
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