Large language models (LLMs) are being used to generate code, improving productivity for developers in various coding tasks. These models are trained on specialized datasets and can fully grasp the context of code through integrated development environments (IDEs). Code-generating LLMs like GitHub Copilot and StarCoder have been shown to produce accurate solutions, including explanations and instructions. However, there is a risk of hallucinations, where generated code may not work as intended or introduce security vulnerabilities. As this technology improves, it's essential to develop strategies for validating generated code and addressing potential issues. The long-term implications of code-generating LLMs on software development are uncertain, but they have the potential to significantly impact how developers work and interact with other team members.