📢 New in LangSmith: Add Experiments to Annotation Queues for human feedback LLMs can be great evaluators, but sometimes human judgment is needed — for example, to gain confidence in your LLM evaluators or to detect nuances an LLM might not pick up on. Now you can instantly queue experiment traces for human annotation. Check out the docs: https://lnkd.in/gp7TTqdh
Great addition! Bridging human insight with LLMs enhances evaluation quality and precision.
Great to see tooling for Human in the Loop support
The new feature in LangSmith that adds experiments to annotations is a fantastic upgrade! It makes tracking, testing, and refining AI workflows much more efficient. This added layer of organization and experimentation is a great step toward creating more robust and reliable AI systems. Exciting to see how this will streamline development for users!