Single vs Multi-Agent AI: Why Most Teams Should Stick With One Agent

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A software architect argues that most teams building AI systems default to multi-agent setups due to framework marketing, not genuine technical need. A single-agent system offers lower latency, reduced cost, and simpler debugging, while multi-agent architectures add coordination overhead and handoff failures. Multi-agent setups do provide real advantages in scope and security isolation when a task genuinely exceeds what one context window can handle. In practical load tests, a five-agent pipeline ran 4–8x slower and cost roughly four times more than a single agent performing the same task. The core advice is to adopt multi-agent architecture only when something specific is broken in a single-agent setup, not as a default design choice.

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