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Maximilien Labonne highlights an open-sourced guide to training models with RL inside real agent harnesses like Claude Code, Codex, and OpenCode, enabling training of any model (e.g., LFM2.5-2.6B) on any task set across harnesses.
DeepSeek Elastic Compute (DSec) is a sandbox infrastructure for effective agentic training of large language models at scale, featuring elastic execution with unified SDK and integration with reinforcement learning frameworks.
TRACE is a new self-improvement approach where an AI agent identifies the missing capabilities behind its own failures and trains itself to address them. TRACE-trained Qwen3.6-27B achieves 73.2% on SWE-bench Verified, outperforming much larger models with fewer training rollouts.