Large Language Models (LLMs) have emerged as powerful tools for automating code generation, offering immense potential to enhance programmer productivity. However, their non-deterministic nature and reliance on user input necessitate a robust understanding of programming fundamentals to ensure their responsible and effective use. In this paper, we argue that foundational computing skills remain crucial in the age of LLMs. We propose a syllabus focused on equipping computer science students to responsibly embrace LLMs as performance enhancement tools. This work contributes to the discussion on the why, when, and how of integrating LLMs into computing education, aiming to better prepare programmers to leverage these tools without compromising foundational software development principles.