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  🚀 TOON vs JSON – The Future of Data Exchange for AI & DevOps Teams As AI and LLM adoption accelerate, developers are exploring smarter data formats beyond JSON. One of the most exciting is TOON (Token-Oriented Object Notation) — a lightweight, token-efficient alternative designed to reduce data size and API token costs in AI workflows. While JSON remains the universal choice for APIs and system integration, TOON shines when working with large structured datasets or LLMs, saving 30–60% tokens in many cases. Here’s a quick look 👇 JSON Example: [ {"id": 1, "name": "Alice", "role": "Engineer"}, {"id": 2, "name": "Bob", "role": "Manager"} ] TOON Example: [2]{Id,Name,Role}: 1,Alice,Engineer 2,Bob,Manager ✅ JSON → Best for integrations, nesting, and interoperability. ✅ TOON → Best for LLMs, prompt efficiency, and structured records. Think of JSON as the reliabl...

 TOON vs JSON: Choosing the Right Format for Your Data and LLM Workflows By Sweta Chakraborty | DevOps Manager | .NET • AI • AWS Cloud | 20+ Years of IT Excellence   In modern software systems, data interchange formats matter more than ever. Whether you’re streaming large volumes of structured records, building microservices, or feeding information into large language models (LLMs), the format you choose can impact readability, maintainability, performance, and cost. For decades, JSON has been the ubiquitous choice. But a newer format — TOON (Token-Oriented Object Notation) — is gaining traction, especially in AI/LLM workflows. Let’s explore both, compare their strengths and weaknesses, and see where each fits best. What is JSON? JSON stands for JavaScript Object Notation. It’s a lightweight, text-based format for representing structured data (objects, arrays, values). It has become a de-facto standard for web APIs, configuration files, and data interchange across languag...