Domain-Specific Languages or simply DSLs are specialized languages designed to bridge the gap between end-users and complex technical systems. By tailoring languages to specific domains, DSLs simplify intricate tasks and democratize access to technology. Through out my career, I have come across many DSLs that were efficient, easy-to-use and transformative.  From managing infrastructure with Terraform to querying data with SQL or configuring Kubernetes with YAML, DSLs have become essential tools for professionals and developers alike.Despite the benefits, DSLs bring some inherent challenges. As number of DSLs grows, the challenges of maintaining and using them efficiently grows as well. Tools like ANTLR have made it easier to create DSLs, but there's still room for improvement especially with the recent advancement of Generative AI. Generative AI offers a promising approach to further enhance DSLs and make them more intuitive and adaptable. I have developed DSL to accomplish one of my domain specific operations and the value they bring from end-user perspective is enormous. At the same time, GenerativeAI has been disruptive force in technology space and became a force-multiplier when it comes to technology usage and evolution.This document explores the evolution of DSLs, the challenges they face, and how the combination of ANTLR and Generative AI can revolutionize DSL development. We'll delve into real-world examples like Presto, a powerful data query engine that uses ANTLR for its robust parsing capabilities. By harnessing the power of these powerful technologies, we can develop more intelligent, user friendly, and efficient DSLs with greater adoption.