<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Cost Saving on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/cost-saving/</link><description>Recent content in Cost Saving on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 15 Nov 2025 03:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/cost-saving/index.xml" rel="self" type="application/rss+xml"/><item><title>Guided Project 2: Optimizing LLM Prompts with TOON</title><link>https://ai-blog.noorshomelab.dev/json-toon-for-ai-guide/project-optimizing-llm-prompts-with-toon/</link><pubDate>Sat, 15 Nov 2025 03:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/json-toon-for-ai-guide/project-optimizing-llm-prompts-with-toon/</guid><description>&lt;h1 id="guided-project-2-optimizing-llm-prompts-with-toon"&gt;Guided Project 2: Optimizing LLM Prompts with TOON&lt;/h1&gt;
&lt;p&gt;In this project, you will experience firsthand the token efficiency of TOON by refactoring a prompt that uses a verbose JSON input into a more compact TOON equivalent. You will measure the token savings and understand how this translates to cost reduction and potentially improved LLM performance.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Project Objective:&lt;/strong&gt; Optimize an LLM prompt for a sales AI agent by converting its data input from JSON to TOON, focusing on token count reduction.&lt;/p&gt;</description></item></channel></rss>