<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>AI Decoded | Erick Ramirez</title><link>https://8567.me/</link><description>Recent content on AI Decoded | Erick Ramirez</description><generator>Hugo</generator><language>en-AU</language><lastBuildDate>Fri, 12 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://8567.me/index.xml" rel="self" type="application/rss+xml"/><item><title>Talk to your database with Bob, the AI builder</title><link>https://8567.me/posts/bob_mcp/</link><pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate><guid>https://8567.me/posts/bob_mcp/</guid><description>Connect Bob IDE to Astra DB via MCP and create collections, insert records, and run bulk updates through plain English, zero code required.</description></item><item><title>Talk to your DB with no code, just Claude</title><link>https://8567.me/posts/claude_mcp/</link><pubDate>Thu, 11 Jun 2026 00:00:00 +0000</pubDate><guid>https://8567.me/posts/claude_mcp/</guid><description>Connect Claude to your DB via MCP and watch it create collections, insert records, and run bulk updates through plain English, zero code required.</description></item><item><title>From Words to Vectors: A Beginner's Guide to Vector Search and AI Databases</title><link>https://8567.me/posts/words_to_vectors/</link><pubDate>Wed, 03 Jun 2026 00:00:00 +0000</pubDate><guid>https://8567.me/posts/words_to_vectors/</guid><description>New to embeddings, LLMs, and vector databases? Start from first principles and end up understanding how modern AI systems search for meaning, not just keywords — with a working Python example.</description></item><item><title>You already trust this DB, let it run your AI stack too</title><link>https://8567.me/posts/already_trust_db/</link><pubDate>Fri, 22 May 2026 00:00:00 +0000</pubDate><guid>https://8567.me/posts/already_trust_db/</guid><description>Bolting a separate vector database onto your operational store creates two schemas, two consistency models, and two failure domains. See why Cassandra keeps it all in one system.</description></item><item><title>You picked the wrong database</title><link>https://8567.me/posts/picked_wrong_db/</link><pubDate>Thu, 21 May 2026 00:00:00 +0000</pubDate><guid>https://8567.me/posts/picked_wrong_db/</guid><description>Not all AI databases are created equal. See how Cassandra runs vector + metadata search in a single query, at scale.</description></item><item><title>About</title><link>https://8567.me/about/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://8567.me/about/</guid><description>About Erick Ramirez</description></item></channel></rss>