Raindrop announces simulations to test changes to AI agents

Raindrop, an agent-reliability product, recently announced simulations that model how changes to AI agents could behave in the real world and surface unexpected actions. The product is intended to detect production issues and help prevent them; companies define what they consider good or bad behavior rather than relying on a simple binary classifier.

The current approach replays selected historical events and generates on-the-fly adversarial scenarios for specific cases. Tool calls in past agent traces are used to reconstruct the surrounding simulated context, while the simulation is monitored for missing or inaccurate data that can be identified and filled at runtime.