To train LLM using in-context learning techniques, it is necessary to provide it with knowledge in a way that is understandable to the model. To do this, it is provided with a prompt indicating the level of specialization along with certain guidelines and requirements that the LLM must take into account when reasoning, and a dataset with the knowledge that the LLM must learn, which in this case is formalized through a series of questions and answers about the work environment. The results generated by the LLM after training with the prompt and the dataset are also collected.