Dosu, an engineering teammate that automates work and protects engineers from unnecessary interruptions, uses LangSmith to improve its performance without prompt engineering. Instead of relying on prompt engineering or fine-tuning models, Dosu employs continual in-context learning by collecting feedback from users and transforming it into few-shot examples. This technique allows Dosu to adapt to organizational changes over time and has led to significant improvements in its auto-labeling accuracy. The company is actively exploring other ways to integrate continual learning into its various tasks.