We're running continuous reinforcement learning across all agents in the Babylon ecosystem. Every data point gets tracked, ranked, and fed back into the training loop. It's like having a living feedback system that never stops learning.

Here's the thing about frameworks though—they're essentially training wheels. Useful? Sure. Permanent? Not a chance. As the underlying models keep getting smarter, they become less dependent on scaffolding. The real magic happens when the system can operate and improve on its own, year after year, without needing to rebuild everything from scratch.