Welcome to the Proof of Usefulness Hackathon spotlight, curated by HackerNoon’s editors to showcase noteworthy tech solutions to real-world problems. Whether you’re a solopreneur, part of an early-stage startup, or a developer building something that truly matters, the Proof of Usefulness Hackathon is your chance to test your product’s utility, get featured on HackerNoon, and compete for $150k+ in prizes. Submit your project to get started! Welcome to the Proof of Usefulness Hackathon spotlight, curated by HackerNoon’s editors to showcase noteworthy tech solutions to real-world problems. Whether you’re a solopreneur, part of an early-stage startup, or a developer building something that truly matters, the Proof of Usefulness Hackathon is your chance to test your product’s utility, get featured on HackerNoon, and compete for $150k+ in prizes. Submit your project to get started! Proof of Usefulness Hackathon spotlight Proof of Usefulness Hackathon spotlight Proof of Usefulness Hackathon Proof of Usefulness Hackathon $150k+ Submit your project to get started Submit your project to get started Today we are interviewing Ali Farhat, the creator behind Token-Efficient JSON for LLMs (TOON Converter). This project solves a common AI engineering problem by converting bulky JSON into a token-efficient TOON format, helping developers save on LLM costs and improve the scalability of their data pipelines. Token-Efficient JSON for LLMs (TOON Converter) What does Token-Efficient JSON for LLMs (TOON Converter) do? And why is now the time for it to exist? Most developers waste a significant portion of tokens when sending JSON to LLMs. This tool converts JSON into a more compact TOON format, reducing token usage and improving efficiency in AI workflows. It is built for developers working with GPT-based systems, automations and structured data pipelines. Now’s a good time for Token-Efficient JSON for LLMs (TOON Converter) to exist because LLM usage is scaling rapidly, and optimizing token consumption is becoming essential for managing production costs and performance. What is your traction to date? How many people does Token-Efficient JSON for LLMs (TOON Converter) reach? Currently receiving around 150 organic users per day through search, ranking #1 for “JSON to TOON Converter”. The audience primarily consists of developers exploring token optimization, LLM integrations and structured data workflows. This early traction validates real demand for more efficient data formats in AI systems. Who does your Token-Efficient JSON for LLMs (TOON Converter) serve? What’s exciting about your users and customers? This tool is built for developers, AI engineers and technical founders working with GPT-style models and structured data. It is especially relevant for teams building automations, agents or pipelines where JSON is frequently passed into LLMs and token usage directly affects scalability and cost. What technologies were used in the making of Token-Efficient JSON for LLMs (TOON Converter)? And why did you choose the ones most essential to your tech stack? The project was built using standard web technologies, primarily relying on Node.js and JavaScript to handle the core conversion logic. These tools were chosen for their ubiquity in web development and seamless integration into existing developer workflows, allowing for rapid deployment and accessibility. Token-Efficient JSON for LLMs (TOON Converter) scored a 65.24 proof of usefulness score (https://proofofusefulness.com/report/token-efficient-json-for-llms-toon-converter) Token-Efficient JSON for LLMs (TOON Converter) scored a 65.24 proof of usefulness score (https://proofofusefulness.com/report/token-efficient-json-for-llms-toon-converter) https://proofofusefulness.com/report/token-efficient-json-for-llms-toon-converter What excites you about this Token-Efficient JSON for LLMs (TOON Converter)'s potential usefulness? * Most developers underestimate how much token inefficiency impacts LLM costs at scale. This project focuses on a very specific but high-impact problem: reducing unnecessary token usage when working with structured data. Even small improvements can lead to significant cost reductions in production systems. What makes this exciting is that it is not theoretical. It directly improves performance, reduces cost, and scales with usage. Meet our sponsors Meet our sponsors Meet our sponsors Bright Data: Bright Data is the leading web data infrastructure company, empowering over 20,000 organizations with ethical, scalable access to real-time public web information. From startups to industry leaders, we deliver the datasets that fuel AI innovation and real-world impact. Ready to unlock the web? Learn more at brightdata.com. Bright Data: Bright Data is the leading web data infrastructure company, empowering over 20,000 organizations with ethical, scalable access to real-time public web information. From startups to industry leaders, we deliver the datasets that fuel AI innovation and real-world impact. Ready to unlock the web? Learn more at brightdata.com. Bright Data: brightdata.com Neo4j: GraphRAG combines retrieval-augmented generation with graph-native context, allowing LLMs to reason over structured relationships instead of just documents. With Neo4j, you can build GraphRAG pipelines that connect your data and surface clearer insights. Learn more. Neo4j: GraphRAG combines retrieval-augmented generation with graph-native context, allowing LLMs to reason over structured relationships instead of just documents. With Neo4j, you can build GraphRAG pipelines that connect your data and surface clearer insights. Learn more. Neo4j: more Storyblok: Storyblok is a headless CMS built for developers who want clean architecture and full control. Structure your content once, connect it anywhere, and keep your front end truly independent. API-first. AI-ready. Framework-agnostic. Future-proof. Start for free. Storyblok: Storyblok is a headless CMS built for developers who want clean architecture and full control. Structure your content once, connect it anywhere, and keep your front end truly independent. API-first. AI-ready. Framework-agnostic. Future-proof. Start for free. Storyblok: Start for free . Algolia: Algolia provides a managed retrieval layer that lets developers quickly build web search and intelligent AI agents. Learn more. Algolia: Algolia provides a managed retrieval layer that lets developers quickly build web search and intelligent AI agents. Learn more. Algolia: Learn more

This story contains AI-generated text. The author has used AI either for research, to generate outlines, or write the text itself. 

Between Two Computer Monitors: This story includes an interview between the writer and guest/interviewee. 

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CodeGraph Earns a 56 Proof of Usefulness Score by Building an Interactive Knowledge Graph for GitHub Repositories

Token-Efficient JSON for LLMs (TOON Converter) Earns a 65.24 Proof of Usefulness Score by Building a Compact Format to Reduce Token Usage

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