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Agents make mistakes. Those mistakes are the most valuable training data there is. Only While. turns them into a dataset, post-trains an open model on it with SFT and RL, and proves the agent stopped repeating them on a held-out test.

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whileai  updated a dataset about 9 hours ago
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whileai  published a dataset about 9 hours ago
while-ai/brand
whileai  updated a Space about 9 hours ago
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While. AI post-training research

Turn agent mistakes into training data. Production traces become a dataset, the dataset post-trains an open model you own, and a held-out test says whether the agent stopped repeating the mistake. The last step is the one most pipelines skip.

Everything here is produced by our open-source SDK and published with the numbers behind it. A model ships when it beats its base on a held-out set with an interval that clears zero. If it does not, it does not ship.

pip install whileai

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