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 →

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 →

Turning Years of Ruby Knowledge Into a Local Coding Assistant

Turning Years of Ruby Knowledge Into a Local Coding Assistant June 1, 2026 Introduction Over the years, most Ruby developers accumulate a vast amount of knowledge. Not just source code, but articles, documentation, experiments, bug fixes, pull requests, design decisions, and lessons learned from maintaining production systems. The problem is that this knowledge often remains … Continue reading Turning Years of Ruby Knowledge Into a Local Coding Assistant →

Running AI Locally for Ruby Development: A Practical Guide with Ollama, Aider, and Your Own Codebase

Running AI Locally for Ruby Development: A Practical Guide with Ollama, Aider, and Your Own Codebase May 28, 2026 Ruby Stack News — by Germán Silva There's a quiet revolution happening in developer tooling, and it doesn't require a cloud subscription, an API key, or sending your proprietary code to someone else's server. Over the … Continue reading Running AI Locally for Ruby Development: A Practical Guide with Ollama, Aider, and Your Own Codebase →

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 →

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 →