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OpenRouter · Experimental AI output
If development teams adopt lightweight RL frameworks like Agent Lightning to train agents with real harnesses, they can accelerate agent improvement but must ensure training environments reflect production constraints.
Compare agent performance metrics in RL training harnesses versus live production workloads to detect simulation-to-reality gaps.
Source evidence
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them with…
Microsoft Research · Oct 7, 2026 ↗
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