ORCHARD

Summary from the TLDR AI newsletter

Orchard is an open-source agentic modeling framework. Its foundation is a thin, Kubernetes-native environment service that exposes generic primitives with no assumptions about the harness, trainer, inference backend, or task domain sitting above it. This foundation allows for recipes that use the same substrate for trajectory distillation, on-policy RL rollouts, and evaluations. Datasets, training recipes, and evaluation protocols stay portable across harnesses, domains, and projects instead of being rebuilt for each new study.