<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Model Fieldnotes — By Swapnil</title><description>Open-source tools, research notes, and practical experiments for people building with AI.</description><link>https://modelfieldnotes.com/</link><language>en</language><item><title>How to compare AI models for your application</title><link>https://modelfieldnotes.com/notes/comparing-ai-models/</link><guid isPermaLink="true">https://modelfieldnotes.com/notes/comparing-ai-models/</guid><description>Start with a real task and a clear definition of success. A useful comparison ends with a decision you can explain.</description><pubDate>Sun, 20 Sep 2026 00:00:00 GMT</pubDate></item><item><title>The cost of a completed task</title><link>https://modelfieldnotes.com/notes/cost-of-a-completed-task/</link><guid isPermaLink="true">https://modelfieldnotes.com/notes/cost-of-a-completed-task/</guid><description>Token prices are only the beginning. Count the tools, retries, and failed attempts behind a useful result.</description><pubDate>Sun, 20 Sep 2026 00:00:00 GMT</pubDate></item><item><title>Reading AI regulation as a builder</title><link>https://modelfieldnotes.com/notes/reading-ai-regulation/</link><guid isPermaLink="true">https://modelfieldnotes.com/notes/reading-ai-regulation/</guid><description>Start with jurisdiction, your role, and the intended use. Learn to separate binding rules, proposals, and voluntary guidance.</description><pubDate>Sun, 20 Sep 2026 00:00:00 GMT</pubDate></item><item><title>When an agent retries a successful action</title><link>https://modelfieldnotes.com/notes/retrying-a-successful-action/</link><guid isPermaLink="true">https://modelfieldnotes.com/notes/retrying-a-successful-action/</guid><description>A missing response does not mean an action failed. Follow one request all the way to two tickets—and the repair that prevents it.</description><pubDate>Sun, 20 Sep 2026 00:00:00 GMT</pubDate></item><item><title>Five foundations for understanding AI agents</title><link>https://modelfieldnotes.com/research/five-foundations-for-ai-agents/</link><guid isPermaLink="true">https://modelfieldnotes.com/research/five-foundations-for-ai-agents/</guid><description>Reasoning and action, learned tool use, context, reflection, and reliability. Five papers that help explain the systems we build.</description><pubDate>Sun, 20 Sep 2026 00:00:00 GMT</pubDate></item></channel></rss>