The text discusses the potential benefits and limitations of large language models (LLMs) for code generation, also known as code-generating LLMs. These tools can help developers be more productive and efficient by providing features such as code completion, explanation, translation, and refactoring. However, there are concerns about privacy implications when using these tools, as internal code may be sent to the model for processing. The author argues that while code-generating LLMs are incredibly useful productivity tools, they will not replace developers entirely, as software development involves more than just coding, including design, architecture, and testing. Instead, developers will continue to use these tools to focus on high-level tasks and review/refactor the generated code.