To overcome the limitations of overly simplistic or emoji-heavy LLM explanations, the author developed a structured pedagogical workflow designed to transform complex technical subjects into interactive simulations. This methodology begins with a "plan mode" using models like Claude (CC) or OpenCode to construct a foundational knowledge base, followed by a critical accuracy review phase to mitigate hallucinations. The core of this process involves prompting the AI to generate a low-poly, "Rollercoaster Tycoon-style" animation that visually maps conceptual stages to physical objects. A practical application of this technique is "ChipTycoon," a web-based simulation hosted on GitHub Pages that tracks the transformation of quartz sand into a finished semiconductor chip through a data center. The simulation provides a visual representation of the manufacturing lifecycle, allowing the user to follow a cart through various industrial stages. To enhance learning retention, the author suggests augmenting these low-poly models with realistic 3D objects derived from image-to-3D transformations and integrating interactive elements such as puzzles or knowledge-based challenges. This approach shifts learning from passive reading of bulleted lists to an active, visual, and spatial engagement with the subject matter.