Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses
TL;DR
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 without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
Nauti's Take
Start with an existing agent and one measurable target, such as tool selection, error rate, or task latency, using a fixed harness. The key checks are integration effort for your tools, reward stability, and whether the training cost produces a better return than simpler prompt or workflow changes.
Sources