<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>LLMind blog</title><description>Announcements and technical writing on file enrichment, LRFS, and AI-readable file formats.</description><link>https://llmind.org/</link><item><title>Implementing an LRFS reader in 100 lines of Python</title><link>https://llmind.org/blog/implementing-lrfs-reader-100-lines/</link><guid isPermaLink="true">https://llmind.org/blog/implementing-lrfs-reader-100-lines/</guid><description>A minimal Python reader for the LLM-Ready File Specification (LRFS v1.0). Parse XMP, canonicalize layers, verify HMAC-SHA256 signatures — under 100 lines, stdlib only.</description><pubDate>Sat, 25 Apr 2026 00:00:00 GMT</pubDate><category>LRFS reader in Python</category></item><item><title>Introducing LLMind: the file enrichment engine</title><link>https://llmind.org/blog/introducing-llmind/</link><guid isPermaLink="true">https://llmind.org/blog/introducing-llmind/</guid><description>File enrichment engine that embeds a signed semantic layer inside files — so any AI tool can read it natively, no vector database required.</description><pubDate>Wed, 22 Apr 2026 00:00:00 GMT</pubDate><category>introducing LLMind</category></item><item><title>What is an LLM-ready file?</title><link>https://llmind.org/blog/what-is-llm-ready-file/</link><guid isPermaLink="true">https://llmind.org/blog/what-is-llm-ready-file/</guid><description>An LLM-ready file carries a signed semantic layer inside its own XMP metadata — any AI tool can read structure, entities, and text without re-parsing.</description><pubDate>Wed, 22 Apr 2026 00:00:00 GMT</pubDate><category>LLM-ready file</category></item></channel></rss>