The 2026 default posttraining recipe for tool-using agents is SFT → DPO → GRPO

Turing Post·medium signal

The consolidated 2026 recipe for capable tool-using agents is a three-stage pipeline: supervised fine-tuning for format and cold-start, preference optimization (DPO/SimPO) for alignment, then RL with verifiable rewards (GRPO/DAPO) for reasoning and generalization. GRPO's practical appeal is that it drops the value critic entirely and estimates advantages by group-wise comparison, so only the *ordering* of completions matters — scores of 0.3/0.5/0.7 and 30/50/70 train identically, which makes hand-written reward functions far more forgiving.