RL gives agents a way to learn from execution.
I think there’s another question worth asking: what happens to the useful knowledge inside those executions after the model gets updated?
Not every lesson should disappear into a weight update. Some should remain traceable and reusable by the next agent.
That distinction is pretty important.
🤷🏻♂️
@ekosproject
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.: msft.it/6019aokV1