Turning a Generic LLM into a Ruby Expert: What RAG Fixed and What It Didn’t

Turning a Generic LLM into a Ruby Expert: What RAG Fixed and What It Didn't June 4, 2026 A practical look at hallucinations, retrieval, and why having the right documentation is not the same as understanding it. Over the past few months, I've been experimenting with a simple question: Can a generic LLM become a … Continue reading Turning a Generic LLM into a Ruby Expert: What RAG Fixed and What It Didn’t →

RubyGems 4.0.13 and Bundler 4.0.13 Released with New Supply-Chain Security Protections

RubyGems 4.0.13 and Bundler 4.0.13 Released with New Supply-Chain Security Protections June 3, 2026 The RubyGems team has released RubyGems 4.0.13 and Bundler 4.0.13, bringing a combination of security improvements, bug fixes, and quality-of-life enhancements for Ruby developers. Built for Ruby on Rails Build Maps WithoutGoogle APIs Generate beautiful production-ready maps directly from your Rails … Continue reading RubyGems 4.0.13 and Bundler 4.0.13 Released with New Supply-Chain Security Protections →

Turning a Generic LLM Into a Ruby-LibGD Expert (One Correction at a Time)

Turning a Generic LLM Into a Ruby-LibGD Expert (One Correction at a Time) June 2, 2026 What a day of conversations taught me about context, memory, and the limits of local AI models. A few days ago, I started what seemed like a simple experiment. I wanted a local LLM to help me work on … Continue reading Turning a Generic LLM Into a Ruby-LibGD Expert (One Correction at a Time) →

The Original Sin, the Scorpion, and Local AI

The Original Sin, the Scorpion, and Local AI June 1, 2026 For the last few weeks, I have been experimenting with local AI models to help me develop and maintain Ruby projects. Built for Ruby on Rails Build Maps WithoutGoogle APIs Generate beautiful production-ready maps directly from your Rails backend. Fast rendering, zero external dependencies, … Continue reading The Original Sin, the Scorpion, and Local AI →

Inside Ruby’s net/http: Exploring the Networking Engine Behind Ruby APIs

May 19, 2026 Most Ruby developers use HTTP every day. Whether through: Rails API integrations webhooks OAuth providers payment gateways microservices REST clients …underneath the stack, many requests still pass through Ruby’s classic net/http. But few developers ever explore how it actually works internally. Inside Ruby’s standard library lives a surprisingly sophisticated networking engine featuring: … Continue reading Inside Ruby’s net/http: Exploring the Networking Engine Behind Ruby APIs →

The AI Art Competition That Nobody Won

The AI Art Competition That Nobody Won April 2, 2026 🚀 See the LIVE DEMO in action MapView Render maps directly from your backend no external APIs required. Fast, controlled, and production-ready. Try the demo → fter teaching different AIs the ruby-libgd interfaces, I proposed a competition: Who could create the most creative and beautiful … Continue reading The AI Art Competition That Nobody Won →

Neither Too Much nor Too Little: A “Touch Base” on the Current State of AI

Neither Too Much nor Too Little: A “Touch Base” on the Current State of AI February 23, 2026 Motivated by the many comments — some fearful, others excessively enthusiastic — about artificial intelligence, I set out to “touch base”: to ground the discussion with a personal perspective on this tool which, no matter how useful … Continue reading Neither Too Much nor Too Little: A “Touch Base” on the Current State of AI →

Building LLM-Powered Applications in Ruby: A Practical Introduction

Building LLM-Powered Applications in Ruby: A Practical Introduction December 12, 2025 (Based on Koichi Ito’s “Ruby × LLM Ecosystem” presentation at Ruby World Conference 2025)** Large Language Models (LLMs) have rapidly evolved from experimental chatbots to foundational components of modern software. They now augment workflows in customer support, content generation, data analysis, and even development … Continue reading Building LLM-Powered Applications in Ruby: A Practical Introduction →

Automating Document Generation with AI in Ruby on Rails

June 3, 2025 In modern software projects, automating routine tasks is crucial to speed up delivery and reduce human error. One great example is document generation—whether it's product requirement documents (PRDs), proposals, or presentations. Recently, I worked on a system that uses AI to generate structured content from conversations, then outputs documents in multiple formats … Continue reading Automating Document Generation with AI in Ruby on Rails →

Enhancing the Trix Editor in Rails with AI-Powered Orthographic Correction

March 14, 2025 Introduction When working with rich text editors in Ruby on Rails applications, enhancing usability is a key factor. Trix is a powerful WYSIWYG editor, but what if we could take it a step further by integrating AI-powered orthographic correction? In this article, I'll walk you through how I built a feature that … Continue reading Enhancing the Trix Editor in Rails with AI-Powered Orthographic Correction →