Stoked to launch 𝚜𝚖𝚒𝚝𝚑𝚝𝚞𝚗𝚎 in public beta! Post-training your agent's policy has never been easier, with training APIs from @baseten and @FireworksAI_HQ becoming increasingly accessible. But sourcing high-quality data to use them effectively remains a challenge. LangSmith processes hundreds of millions of traces a day, making it a rich system of record for your agent’s behavior. 𝚜𝚖𝚒𝚝𝚑𝚝𝚞𝚗𝚎 turns those trajectories into the data you need for supervised fine-tuning, with an end-to-end pipeline for curation, preparation, training and deployment for models you want to SFT for specific tasks. We care deeply about giving teams ways to own their own intelligence, and as the open model frontier continues to advance, it’s becoming increasingly clear that post-training on your own agent data will become a key part of that. Excited to get this into people's hands!