How I use LLMs to learn complex topics

	How I use LLMs to learn complex topics(laurentiugabriel.github.io)
	795 points by laurentiurad 12 days ago \| 530 comments
	tl;dr: The author uses LLMs to learn complex topics by prompting them (via Claude Code/OpenCode) to first build and verify a foundational knowledge base, then generate a low-poly, RollerCoaster Tycoon-style interactive simulation of the process, hosted on GitHub Pages. They've applied this to chip fabrication (ChipTycoon), rocket engines, LLMs, F1 engines, and EUV machines, arguing that visual simulations aid retention better than text explanations, and suggest enhancements like photo-to-3D object mapping and quiz challenges.
	HN Discussion: ↓LLM learning posts lack proof of actual acquired capability and may create illusion of learning ↓The claim that animations are hallucination-free is unconvincing since AI checks its own work ↓The RollerCoaster Tycoon-style animations add little value over plain text lists ~Socratic dialogue or literate code rewrites are more effective LLM learning methods than simulations ↓Deep learning requires hands-on tacit knowledge and boring details that LLMs cannot shortcut