Let's build the GPT Tokenizer. When Andrej Karpathy left OpenAI last week a lot of people expressed hope that he would be increasing his output of educational YouTube videos.
Here’s an in-depth 2 hour dive into how tokenizers work and how to build one from scratch, published this morning.
The section towards the end, “revisiting and explaining the quirks of LLM tokenization”, helps explain a number of different LLM weaknesses—inability to reverse strings, confusion over arithmetic and even a note on why YAML can work better than JSON when providing data to LLMs (the same data can be represented in less tokens).
Recent articles
- First impressions of Claude Cowork, Anthropic's general agent - 12th January 2026
- My answers to the questions I posed about porting open source code with LLMs - 11th January 2026
- Fly's new Sprites.dev addresses both developer sandboxes and API sandboxes at the same time - 9th January 2026