We updated our post-CS1 course that introduces various subfields of computer science so that it integrates Large Language Models (LLMs). The course now includes explicit instruction on how LLMs work, exposure to current AI tools and ethical issues, and student re- flection on personal use of LLMs and the larger evolving landscape of AI. We demonstrate the use and verification of LLM outputs, guide students in the use of LLMs within a larger problem-solving loop, and require disclosure of the nature and extent of LLM as- sistance. Throughout the course, we discuss risks and benefits of LLMs across CS subfields. In our first iteration of the course, we collected and analyzed data from students' pre and post surveys. Student understanding of how LLMs work became more technical, and their verification and use of LLMs shifted to be more discerning and collaborative. These strategies can be used in other courses to prepare students for the AI-integrated future.