On January 9, 2026, SETA announced 400 training environments, a reinforcement-learning pipeline, and SETA-RL-Qwen3-8B weights for terminal-agent experiments.
On January 9, 2026, SETA announced 400 training environments for terminal agents, a reinforcement learning (RL) training pipeline, and the weights for the SETA-RL-Qwen3-8B model. The post also describes the CAMEL toolkit’s terminal harness as state of the art on terminal-bench—a characterization by SETA, not an independent assessment reported in the source.
The release may interest engineers researching terminal-agent training. To confirm scope, availability, and results, consult the original announcement and check the materials and evaluation criteria published by SETA; the report provides no detailed metrics. If you use AI to study or apply the material, do not put internal data or credentials in prompts: Rota Nacional applies data-protection policies before models run.