With recent advances in AI, novel methods like generative AI and large language models have captured significant attention. However, Agent-Based Modeling (ABM) offers unique advantages and versatility for various applications such as financial modeling, social interactions, and cybersecurity. In this talk, I aim to demonstrate the potential of ABM for fast experimentation and hypothesis testing by modeling the world through isolated, manageable components. By breaking down complex systems into simpler elements, ABM allows for easier exploration and understanding of the underlying dynamics. I will showcase various use cases and provide Python code snippets using the Mesa package to illustrate the practical implementation of ABM. Join me in discovering the untapped potential of Agent-Based Modeling and learn how to implement this powerful approach in your projects with the help of Python and the Mesa package. As an exciting bonus, I'll also demonstrate how to integrate GPT within ABM, because everyone wants a piece of GPT in their projects!