Tahuna debuts CLI-first control plane for post-training workflows

Tahuna fills a critical gap in the MLOps stack by decoupling training logic from infrastructure orchestration, offering a "gentle control plane" that prioritizes researcher flexibility over rigid frameworks. It simplifies the transition from local prototyping to large-scale compute by handling provisioning, synchronization, and artifact persistence while focusing specifically on the post-training bottleneck. The CLI-first architecture and support for ecosystems like PyTorch, Hugging Face, and Unsloth position it as a developer-centric alternative to heavyweight enterprise ML platforms.