Mailmind case study: Multi-agent AI orchestration prevents deadlocks, powers email assistant

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A case study on the fictional Mailmind AI email assistant illustrates multi-agent orchestration, where specialized AI models cooperate on tasks. This approach coordinates separate agents for distinct jobs like email triage, drafting, and review, preventing them from stalling. The article details two coordination patterns: sequential pipelines for dependent tasks and manager-worker setups for parallel jobs. It explains that preventing agent deadlock requires specific system design, not just improved prompts. The concepts are grounded in the practical example of an AI system that reads, summarizes, and replies to emails.

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