If you’re a premium subscriber Add the private feed to your podcast app at https://add.lennysreads.com You’ve probably heard terms like LLM, transformer, and hallucination, but do you really know what they mean? In this episode, I walk through 20 of the most common AI terms with dead-simple explanations you can actually understand (and use). In this episode, you’ll learn • What a “model” actually is • The difference between pre-training, fine-tuning, and RLHF • What transformers are—and why they changed everything • How prompt engineering and RAG improve model outputs • What AGI and ASI really mean • The difference between LLMs, GenAI, and GPT • Why models hallucinate (and how to prevent it) • What synthetic data is—and why it matters • How vibe coding works and what agents can actually do • What MCP, inference, and tokens are in plain English Referenced • A complete guide on RLHF • AGI vs ASI • Andrej Karpathy on LLMs • Andrej Karpathy on vibe coding • Anthropic’s guide on building effective agents • Anthropic’s guide to reducing hallucinations • Fine-tuning vs RAG vs prompt engineering • Guide to model context protocol (MCP) • How LLMs work • How fine-tuning works • How top models tokenize words • How training and pre-training works • Ilya Sutskever on AGI • Ilya Sutskever on next-word prediction • Lenny’s Podcast on prompt engineering • Make product management fun again with AI agents • RLHF explainer • Sam Altman on synthetic data • Technical deep dive on transformers • What are transformers? Subscribe: YouTube | Apple | Spotify Follow Lenny: Twitter/X | LinkedIn | Podcast About Welcome to Lenny’s Reads, where every week you’ll find a fresh audio version of my newsletter about building product, driving growth, and accelerating your career, read to you by the soothing voice of Lennybot. To hear more, visit www.lennysnewsletter.com
