Outcome-driven learning systems: Enterprise RL with OpenEnv and Foundry
Microsoft Foundry assembles agents, tuning, evals, and OpenEnv into an owned reinforcement-learning loop that improves over time.
“the durable asset is not the model you rent, it is the learning loop you own”
Microsoft's AI Foundry blog frames its Build 2026 releases (hosted agents, fine-tuning, Frontier Tuning, OpenEnv integration) as components of an owned, self-improving 'learning system' rather than a static model. It positions enterprise RL and a modular hill-climbing loop—combining non-parametric and parametric optimization—as the durable competitive asset, signaling a strategic shift toward customer-owned learning loops over rented models.