@Teknium: Interesting insights, especially this: Hermes starts off as any other agent does, inefficient and often not sure how to…

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Summary

Teknium observes that the Hermes agent initially behaves inefficiently but gains large efficiency boosts after solving a task once, likening it to "linearized RL."

Interesting insights, especially this: Hermes starts off as any other agent does, inefficient and often not sure how to complete a task that is training didnt have priors for. However, solve it once and you unlock huge efficiency gains. I sometimes call this linearized RL,
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Cached at: 04/21/26, 05:13 PM

Interesting insights, especially this: Hermes starts off as any other agent does, inefficient and often not sure how to complete a task that is training didnt have priors for. However, solve it once and you unlock huge efficiency gains. I sometimes call this linearized RL,

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