March 4, 2025
Why Post-Training Matters Now: From SFT to RFT
In today’s competitive AI landscape, customization of foundation models has become essential for organizations seeking to create differentiated value. As using the same models as competitors leads to commoditization, post-training techniques have emerged as critical tools that allow enterprises to tailor models to their specific needs without incurring the prohibitive costs of building models from scratch. Among these techniques, Supervised Fine-Tuning (SFT) and Reinforcement Fine-Tuning (RFT) represent two distinct approaches with unique strengths and applications. The economics of model customization have shifted dramatically in favor of post-training methods, with efficiency gains increasingly derived from strategic adaptations rather than developing entirely
