With the introduction of Large Language Models (LLMs) and their integration with software development tasks, the software development landscape has changed drastically in the last couple of years. In this session, we delve into the intricate world of large language models for code (LLMs4Code) and explore their benefits, challenges, and threats. On one hand, these models have revolutionized code completion, bug detection, and even generated entire sections of code with remarkable accuracy. However, on the other side, several concerns have emerged surrounding inaccurate, buggy, and vulnerable code generation, biases, implications for climate, and the potential for unintended consequences. Together, we’ll dissect real-world examples, discussing the transformative power of large language models while exploring the gray side of LLMs4Code that developers tread. The talk will discuss strategies for effectively leveraging these tools, mitigating risks, and contributing to the ongoing dialogue about responsible AI in the coding ecosystem. The talk promises an exploratory take that not only seeks to harness the potential of LLMs4Code but also ensures a conscientious and mindful approach toward their integration into our coding practices.