Large Language models and Generative AI have taken the world by storm with their ability to generate coherent and diverse text, speech, images and more. These models, however, are not perfect and suffer from limitations such as data bias, lack of creativity, and low variability in output. In this talk, we will delve into the nuances of large language models and generative AI, exploring the impact of prompt engineering on the models' outputs. We will also discuss the strategies that can be employed to improve the models and tackle these limitations, including data augmentation, fine-tuning, and multi-model ensembling. By the end of this talk, attendees will gain a deeper understanding of the potential and limitations of these models, and the steps they can take to enhance their outputs and write prompts in a efficient way