Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses
3,500 lines. That's all Agent Lightning needs to connect existing agents to RL training without rebuilding them.
Why it matters
Microsoft Research releases a lightweight framework that lets practitioners improve deployed agents through reinforcement learning without rearchitecting their existing harnesses—addressing a real friction point in agent optimization.
The key facts
11 to knowAgent Lightning v1.0 released by Microsoft Research
3,500-line lightweight codebase
Connects existing agents to RL training without requiring framework rebuilds
Designed to manage tools, context, and decision-making without complex framework overhead
Solves the challenge of improving agents post-deployment while preserving existing harness architecture
Published October 7, 2026
3,500-line lightweight framework
Connects existing agents to RL training without framework rebuilding
Manages tools, context, and decision-making externally from RL loop
Published by Microsoft Research
v1.0 release (October 7, 2026)
Go to the source
Microsoft Researchmicrosoft.com
Publisher excerpt: 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.