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Patrick Jiang
@patpcj
CS PhD @ UIUC @siebelschool, Research Fellow @AnthropicAI; prev: SR @GoogleResearch; recent work: DeepRetrieval, s3, R4T, Context-1, Harness-1 (w/ @trychroma)
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Jun 6
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14 tweets
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5 min read
Introducing Harness-1, a 20B search agent trained with a state-externalizing harness.
> frontier-level long-horizon search, rivaling Opus-4.6 and outperforming GPT-5.4
> Context-1-level cost and latency
> externalizes candidates, evidence, verification, and search history
> open-source
[1/N] I’ve been wondering:
maybe search agents are bad at search partly because we make them do all the paperwork in their head.
So I tried a simple idea:
externalize the search state, then train the model to use that harness.
The result is Harness-1: a 20B search agent that can match or even beat much larger frontier AI on hard long-horizon search tasks.