Multi agent vs Single Agent systems

Reddit r/AI_Agents News

Summary

The article argues that most 'agentic' systems are actually single agents with tools, highlighting the high costs and complexity of multi-agent setups. It outlines three valid multi-agent patterns—orchestrator-worker, pipeline, and peer-to-peer—and provides criteria for deciding when to use them versus a single agent.

Most things people call "agentic" are one good agent in a loop with two or three tools. Multi-agent adds real cost more latency (each handoff is a network call), more token spend (each agent rereads context), more failure modes (any worker can return garbage), more debugging surface (bad output could come from any of five places). Three patterns that actually exist: Orchestrator worker: one agent plans and delegates, specialized workers each handle one piece. Research agent pulls competitor data, copywriter drafts copy, image agent makes the hero asset, reviewer checks tone and claims. Each worker has a narrow job and only the tools it needs. Right shape when steps are genuinely different jobs needing different specialists. Pipeline: linear handoff. Agent A finishes, B starts on A's output, C on B's. Support ticket comes in classify intent, extract customer ID, draft reply, check tone. Simple to debug because each stage has one input and one output. Use when steps are independent and order is fixed. Peer2peer: multiple agents argue toward consensus. Three code reviewers read the same PR one for correctness, one for security, one for readability. A judge agent reads all three and decides what blocks merge. Use when no single perspective is enough and disagreement improves the answer. Note these points: * Are the steps genuinely parallel where running them simultaneously saves real time? * Do different stages need different tools or prompts that can't fit in one agent? * Do you need a critic separate from the actor? Two or more yeses is multi-agent. One or zero use single agent with good tools.
Original Article

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