#  Introduction   JSON is great for APIs, storage, and application logic. But inside large language model (LLM) pipelines, it often carries a lot of token overhead that does not add much value to the model: braces, quotes, commas, and repeated field names on every row. TOON , short for Token-Oriented Object Notation, is a newer format designed specifically to keep the same JSON data model while using fewer tokens and giving models clearer structural cues. The official TOON docs describe it as a compact, lossless representation of JSON for LLM input, especially strong on uniform arrays of objects. In this article, you will learn what TOON is, when it makes sense to use it, and how to start using it step by step in your own LLM workflow. We will also keep the tradeoffs honest, because TOON is useful in some cases, not all of them. #  Why JSON Wastes Tokens in LLM Pipelines   JSON becomes expensive in prompts because it repeats structure over and over again.…