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Princeton paper finds combined specialist agents from many developers beat a general agent on GAIA

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A Princeton paper reports that combining specialized agents built by different developers reached 70% accuracy on GAIA, where each specialist alone scored at most 35%. Under the same total development budget, this combined system beat the median general-purpose agent by 12 points. On SealQA, a web-search-only benchmark, the combined system performed worse at higher cost.

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New Princeton paper finds that combining specialized agents from many developers can beat any single developer's general agent, with GAIA accuracy reaching 70%.

Today most agentic systems are built and controlled by 1 developer, so each team rebuilds the same basic skills. The authors argue this limits scale.

They simulated populations of developers with LLM agents that build agents under a fixed budget, then compared lone systems with a multi-developer system. The multi-developer system splits each task and routes the parts to different developers' agents.

On GAIA with the same total development budget, specialists that each scored at most 35% alone reached 70% together. That is 12 points above the median general agent, while on web-search-only SealQA the combined system did worse at higher cost.

Build agents to fill gaps in shared systems, since an agent scoring 19% alone lifted a combined system from 40% to 53%.

Source: Rohan Paul · x.comPublished