We spent a lot of time streamlining the process to go from your agent's trajectories to an SFT'd model on your training/inference provider o…

We spent a lot of time streamlining the process to go from your agent's trajectories to an SFT'd model on your training/inference provider of choice so you don't have to stitch together the steps manually. The data curation phase is definitely the most important, and we've had great results from working with training copilots in the form of model councils and a coding agent guided by the CLI and its packaged skills. This + the good ol' fashioned 'look at the data' ring true for any well-designed eval & post-training pipeline, and we're really excited to enable builders to use this in the process of owning your own intelligence! Last week, we launched LangSmith Fine-Tuning and the smithtune CLI. Turn your agent’s own trajectories into a fine-tuned model without building a training pipeline by hand. Your traces already show your agent doing the job well. Now, that signal becomes training data. Quick demo …

Source: Harrison Chase (X) | 2026-10-01