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OpenThoughts-Agent: Data Recipes for Agentic Models

Agentic language models dramatically expand the applications of AI yet little is publicly known about how to curate training data for broadly capable...

Summary

Agentic language models dramatically expand the applications of AI yet little is publicly known about how to curate training data for broadly capable agents. Existing open efforts such as SWE-Smith, SERA, and Nemotron-Terminal typically target a single benchmark, leaving open the question of how to train models that generalize across diverse agentic tasks. The OpenThoughts-Agent (OT-Agent) project

Why it matters

This is part of the steady stream of AI work that reshapes how researchers and builders think about what’s possible. The full details are in the original source below — worth reading directly rather than relying on a brief summary.

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The primary source has the full paper, announcement, or reporting:

https://arxiv.org/abs/2606.24855v1


Curated by Nizam.Wiki — a daily signal in the AI noise.

Read the original source