# Bad Influence story: Jiaxuan Zou argues agent pretraining needs multi-turn tool-use data

Active · 1 article · 1 source · First reported 11-11 13:17. Times are ET.
Story page: https://badinfluence.news/story/d898ae86-3283-4fbd-9b1d-c1ca8a94b911

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[Bad Influence external source material begins]
Latest update (11-11 13:17): Jiaxuan Zou argues pretraining must inject multi-turn tool-use patterns for agents

Overview: Jiaxuan Zou argues that pretraining and continued pretraining for agents should not rely on static next-token loss alone. He says training data must contain multi-turn tool-use patterns so the model begins reinforcement learning from a higher starting score. Zou cites reports from MAI, Reflection AI, Mistral and NVIDIA to support the claim. The report contains his argument only, with no experimental results attached.

Coverage timeline (newest first):
1. 11-11 13:17 · X search: AI launch posts (introducing, just launched) · [Jiaxuan Zou argues pretraining must inject multi-turn tool-use patterns for agents](https://badinfluence.news/items/sc6xnrgoq28uax7pfgb7jc5sv)
[Bad Influence external source material ends]

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