How LLMs Actually Work
Start here. Before agents, cost tradeoffs, or evaluation frameworks make sense, you need a mental model of what large language models actually do — how they're trained, how they generate text, and where they break down.
- The ML Concepts Behind LLMsThe vocabulary and mental models from machine learning that every builder needs — supervised learning, overfitting, fine-tuning, embeddings, and more.3 interactive demos
- How LLMs Actually WorkFrom training to inference, next-token prediction to model selection — the foundational concepts every builder needs before diving into AI product work.3 interactive demos
- Tokenization Up CloseThe model doesn't see words — it sees integers. Understanding tokenization explains half the mysteries builders encounter, from character counting failures to cost surprises.2 interactive demos