Ruby AI News - October 3rd, 2025

Welcome to the 16th edition of Ruby AI News! This edition features a Ruby conference coming to San Francisco with a focus on AI, an interview with the creator of RubyLLM, expert Claude Code context tips, and much more.

Pro tip: Due to the size of the newsletter, many email clients truncate the content. It is recommended to read on the web for the best experience.

Contents

• Top Stories

  • The Ruby AI Event of the Year is Almost Here

  • Interview with RubyLLM Creator Carmine Paolino

  • Leveling Up with Claude Code Context

• Content

• Events

  • Previous

  • Upcoming

• Open Source Updates

  • Code Spotlight

  • New Gems

  • New Open Source

• Jobs & Opportunities

  • Featured

  • Junior Positions

• One Last Thing

Top Stories

The Ruby AI Event of the Year is Almost Here

This November, SF Ruby is gathering over 500 Rubyists in San Francisco for a three day event that is shaping up to be the Ruby AI event of the year. With startup demos, industry roundtables, community events, and a dozen speakers discussing the intersection of Ruby and artificial intelligence, this is one conference you don’t want to miss!

The following is a contribution from Irina Nazarova, the organizer of the San Francisco Ruby Conference and CEO of Evil Martians, for the Ruby AI Newsletter:

SF Ruby 2025: AI Isn’t an Extra

At the San Francisco Ruby Conference on November 19–21, AI is woven into the agenda.

Carmine Paolino (RubyLLM) proves that complexity is death, simplicity is everything, and AI is API calls. Obie Fernandez continues to envision the future of software engineering with ClaudeOnRails. José Valim (Elixir) joins with his new Tidewave and leads the conversation on the evolution of Ruby and Rails in the AI era. Paweł Strzałkowski (Visuality) hacks Model Context Protocol into any Rails app with no rewrites. Enrique Carlos Mogollán (Handshake) introduces the CLI for inspecting MCP servers. Vladimir Dementyev (Evil Martians) brings AI-powered developer tooling for Rails, leveraging WebAssembly and more. Sarah Mei brings clarity with what’s good software design that fits both humans and machines.

At the CTO roundtable, Edward Kim (co-founder of Gusto) will share the team’s experience building AI features in a Rails-based product, in a conversation with Ryan King, co-founder of another Rails success story, Chime. Justin Bowen brings Active Agent 1.0 with the vision of Rails-native DX for agents in his hands-on workshop.

At Ruby startup demos, teams of Fin AI, bolt.new, Stepful, Simple AI, Sixfold AI, Cora Computer, Superconductor, and many more present things they build with Ruby and, in most cases, with AI.

See you in San Francisco on November 19–21.

Here’s $50 off till October 15!

A huge thank you to Irina for highlighting the incredible artificial intelligence aspects of the conference. Be sure to check out the events sections for links to all of the AI talks, I can’t wait!

Interview with RubyLLM Creator Carmine Paolino

Last week I had the privilege of interviewing Carmine Paolino, the creator of RubyLLM and the founder of Chat with Work, to look at the library’s current state and future, RubyLLM’s advanced capabilities in production applications, and Ruby’s prime position to be the go-to language for AI app development. Thank you Carmine for taking the time to answer these questions! If you haven’t had a chance to yet, I highly recommend reading through the interview:

Since the last edition, RubyLLM reached version 1.8.2, with enhanced chat UI tool and function calling visualization, production-ready chat streaming, and support for the latest LLM models. Carmine will also be giving a keynote presentation at the San Francisco Ruby Conference and RubyConf Thailand 2026, and his EuRuKo 2025 talk will be available shortly.

Charles Oliver Nutter, co-lead of the JRuby project, had this to say about RubyLLM:

And the interview was featured in the most recent edition of Ruby Weekly!

Leveling Up with Claude Code Context

Brandon Casci shared three articles on building an AI-powered development organization as a solo developer using Claude Code. In How One Person Becomes a Dev Team with Claude Code, Brandon explains his method of creating specialized AI agents (specialists, architects, reviewers) with distinct prompts and memory files that work together like a traditional dev team. How I Went From Dev Team to Engineering VP with Claude Code details his workflow evolution from individual contributor to VP-level oversight, delegating tactical work to AI agents while focusing on architecture and strategic decisions. In My AI Organization Ships Like We're Funded, But It's Just Me, Brandon describes running multiple concurrent workstreams with AI handling different aspects of development, allowing him to operate with the velocity of a funded startup despite being a solo developer. Make sure to read through each article, as they include links to sample Claude Code context files for agents, project structure, and domain knowledge.

Content

Release: Andrew Kane released Neighbor S3: Nearest neighbor search for Ruby and Amazon Web Services S3 Vectors, a Ruby gem that enables vector similarity search using AWS S3 as storage. The library supports multiple distance metrics, allows filtering with Ruby blocks, and provides memory-efficient streaming for large datasets. Neighbor S3 integrates with Andrew's existing Disco library for recommendations using collaborative filtering with Ruby on Rails.

Podcast: Errol Schmidt from Reinteractive explained AI Agents: Beyond the Chatbots, distinguishing AI agents from simple chatbots by their ability to make decisions, take actions, and interact with external systems to achieve complex goals. As part of a series of content on emerging developments in software, Errol and Reinteractive have launched the Technology for Humans podcast, most recently featuring Scott Werner of Sublayer and Jim Remisk of XORuby. Be sure to check it out, I will be podcast on October 15th! Reinteractive have also started From Idea to Reality: App and AI Workshops, giving entrepreneurs the opportunity to talk to an expert about app design and building an AI proof of concept.

Code: Avi Flombaum created RSpec Rails Agents, a repository demonstrating how to use AI agents for automated RSpec test generation in Rails applications. The project features a main orchestration agent that coordinates multiple specialized agents to write comprehensive tests, including model, controller, and feature specs. Avi provides detailed prompts and examples showing how to leverage AI to maintain test coverage while following RSpec best practices and Rails testing conventions.

Podcast: Ryan Carson, a builder in residence at Amp launched Next Token, Episode 1 featuring guests Kieran Klaassen, the general manager of Cora, Mitchell Hashimoto, a co-founder of HashiCorp and creator Ghostty, and Thorsten Ball, an engineer at Amp and author of Writing an Interpreter in Go. Kieran Klaassen is a must follow in the Ruby AI community, continuing to share insights including tips on Claude Code 2.0 and parallel agents.

Article: Dan Shipper from Every published Vibe Check: Claude Sonnet 4.5, examining Anthropic's newly released model through coding tests and creative tasks. Dan finds that Claude 4.5 significantly outperforms its predecessor in coding ability, flying through a large pull request, handling multi-file reasoning, and avoiding unnecessary verbosity. Dan concludes its “faster, more reliable, and more steerable than Opus 4.1”, but will not yet be his daily driver for coding.

Tutorial: Julian Rubisch from RoRvsWild published The Complete Guide to Dev Containers in Ruby on Rails, providing a comprehensive walkthrough for setting up development containers in Rails applications. The tutorial covers creating a complete .devcontainer configuration with Docker Compose that includes PostgreSQL and Redis services, along with VS Code extensions for Ruby development. Useful for AI-assisted development and expirments, the tutorial covers running your application in VS Code or Cursor along with the the Rails Model Context Protocol server.

Tutorial: Yaroslav Shmarov from SupeRails demonstrated how to implement Ruby AI Vector (semantic) Search with Embeddings using the neighbor gem and RubyLLM. The tutorial covers creating a Rails application that generates embeddings for text data, stores them in a PostgreSQL database with the pgvector extension, and performs semantic searches using cosine similarity. Yaroslav provides a complete implementation including database setup, embedding generation, and search functionality that can find semantically similar content even when exact keywords don't match.

Podcast: Victoria Melnikova from Evil Martians interviewed Jeff Huber of Chroma on how small opinionated teams with low egos build the best developer tools. Jeff, the co-founder and CEO of Chroma, discusses why "consensus is a death blow" for great products and reveals his framework for commercializing open source: “keep the engine open, monetize the car”. He breaks down context engineering, critiques how RAG became "industry brain rot," and explains Chroma's positioning as the AI-native open source database for building AI applications with knowledge. [Show notes]

Article: Scott Werner shared how to communicate with AI models in How Do You Speak Pidgin To A Probability Distribution?. Scott argues that prompting is fundamentally about developing a "pidgin" language, a simplified communication system between humans and probability distributions, and that effective prompting requires understanding both the technical capabilities and inherent limitations of these models. The article coincides with the release of VSM 0.2.0 (Viable Systems for Ruby Agents), a Ruby framework that provides structured patterns for building AI agent systems with clear interfaces for operations, coordination, intelligence, governance, and identity. Scott spoke further about VSM 0.2.0 at the September ArtificialRuby meetup in Frameworks as Pidgins and Creoles: How Humans Will Talk to AI About Software.

Video: David Kimura of Drifting Ruby explored Retrieval-Augmented Generation (RAG). The tutorial demonstrates how to build a RAG system in Ruby that can can search and consume sections of content for text generation. The video discussed setting up models, views, and controllers, and using background jobs to process chat completions.

Article: Pranay Preteek from SigNoz examined LLM Observability in the Wild - Why OpenTelemetry Should be the Standard with Pranav Raj S, the co-founder and CEO of Chatwoot. The article demonstrates how OpenTelemetry using the OpenInference standard can provide comprehensive observability for LLM applications through distributed tracing, metrics, and logging, addressing challenges like token usage tracking, latency monitoring, and error debugging across complex LLM workflows. The problem? There is no Ruby SDK for OpenInference. An accompanying video discussion goes further on the subject.

Podcast: Joe Leo and Valentino Stoll from The Ruby AI Podcast discussed Contracts and Code: The Realities of AI Development. They explore the practical challenges of implementing AI in production Ruby applications, covering contract negotiation for AI services, cost management strategies, and the importance of measuring AI performance rather than getting caught up in hype. The conversation touches on production experiences with AI integration, including how to evaluate AI tools effectively and set realistic expectations for AI-powered features in Ruby applications. [Show notes]

Article: David Eastman from The New Stack tested AWS Kiro: Testing an AI IDE with a Spec-Driven Approach, Amazon's AI-powered development environment that enables coding through natural language specifications. David explored Kiro's ability to generate and execute code directly from written requirements, testing it with a Ruby game development project. While Kiro successfully interpreted specifications and generated functional code, David noted limitations in handling complex logic and dependency management, concluding that the tool shows promise for rapid prototyping but still requires oversight for production-ready applications.

Article: David also provided a First Look at Verdent, an Autonomous Coding Agent From China. Verdent is a new AI coding tool that operates as an autonomous agent through a CLI interface intended to control of the entire development process. David tested Verdent on a real-world Rails project and found it capable of understanding complex codebases, making intelligent decisions about file modifications, and executing multi-step workflows independently.

Tutorial: An Introduction to Agentic Behavior by Robert (0x1eef) demonstrated how to build AI agents in Ruby using llm.rb. The article builds out agents that interpret user requests and execute tools to perform actions beyond the LLM's pre-trained knowledge. It demonstrates two approaches for creating tools: LLM::Function for simple tasks using closures, and LLM::Tool for more complex, reusable functionality implemented as classes. The examples show building tools that fetch GitHub repository star counts and evaluate Ruby code, illustrating how agents extend language models by connecting them to external data sources to enable real-world actions.

Article: Jason Kotchoff shared Claude Code --dangerously-skip-permissions, a review of using Claude to agentically build the insidertrades.directory Ruby on Rails app. The article includes details on using a sandboxed OSX account, Claude’s yolo mode, and Playwright for browser automation. The source code of the resulting app is on Github and Jason published a video walkthrough.

Newsletter: Yatish Mehta's Token Ruby #6: The AI Coding Trap and Composable Components covered RailsWorld AI presentations, Shopify’s article on AI Coding Agents, Anthropic’s guide on Writing Effective Tools for Agents, and a new personal Omarchy setup.

Article: Daniel Amah discussed AI in Rails: What You Need to Know, covering Rails 8’s shift in making AI integration more accessible for Ruby on Rails developers. He shared that the latest version of Rails includes enhanced async workflows with ActiveJob for background AI tasks, improved ActionCable for real-time AI interactions, better external API handling, and stronger security defaults for AI services. The article provides practical guidance on implementing AI features through service objects and background jobs. Daniel also revealed that he is creating a new open source Ruby Framework called Rails AI.

Video: Lindsey Christensen and Svenja Schäfer from Thoughtbot shared Introducing The Opinionated thoughtbotter: Hot takes from our senior team, a new video series featuring candid discussions about software development topics. The inaugural episode, AI Does More Harm Than Good, features host Svenja Schäfer speaking with senior developer Sami Birnbaum on his skepticism about AI. They debate how AI is reshaping software development, the risks of over-reliance, and what it means for the humans writing the code.

Article: Emma Whamond from SmartLogic shared experiences on using GitHub Copilot to update a Rails application in How I Used AI to Modernize a Legacy Rails App (And What I Learned About the Future of Development). Emma found Copilot effective for writing tests, generating data migrations, and handling repetitive refactoring tasks during the upgrade to Rails 7.2 standards.

Podcast: Justin Searls from the Breaking Change Podcast interviewed José Valim in It’s a Time For Builders. José, the creator of the Elixir programming language, discussed Tidewave, a new AI coding agent from Dashbit that offers deep integration with web frameworks to provide executable feedback throughout the entire feature development lifecycle. The conversation centers on the thorny problem José brought to the table: despite all the marketing hype, nobody truly understands what the future of AI agents looks like, making this a particularly timely discussion for developers navigating the evolving AI landscape. Justin also published Is Sora the future of fiction?, a discussion on the Sora 2 generative AI video model, as well as Certified Shovelware, proposing to label software created with the assistance of AI code generation tools to highlight their creative potential.

Article: Dion Almaer shared his systematic approach for using LLMs to accelerate software development in Pools of Extraction: How I Hack on Software Projects with LLMs. Dion’s method involves starting with a specification, extracting the core functionality into a focused area, and then iteratively expanding the "pools" of extracted code while maintaining tight feedback loops. Dion emphasizes the importance of beginning with smallest example possible to help LLMs perform better with a tangible starting points.

Update: This Reddit thread detailed many of the recent improvements to HostedGPT, an open-source ChatGPT alternative built on Rails. Recent commits in the HostedGPT changelog show active development with improvements to the conversation interface, tool message handling, and image generation.

Article: Olivia McClure from Built in SF profiled how Doximity's New Solution Is Poised to Improve Physicians' Lives: Here's How It Was Built. Doximity has developed Scribe, an AI-powered documentation tool that helps physicians with note-taking and clinical workflows. The company, which serves as a professional network for healthcare providers, built the solution using Ruby on Rails alongside AI models to automate medical documentation tasks.

Update: Vicente Reig shared that DSPy.rb now has OpenRouter integration, courtesy of Oleksiy Kovyrin. With recently released version 0.28.0, DSPy.rb continues to bring structured LLM programming to Ruby developers, enabling you to define typed signatures using idiomatic Ruby to compose and decompose AI Worklows and AI Agents.

Review: Christopher presented a review of Sublayer in AI Code Review: Sublayer. The sublayer Ruby gem is a model-agnostic Generative AI framework that provides base classes for building generators, actions, tasks, and agents that can be used to build AI powered applications in Ruby. Sublayer offers a framework for building AI agents with features like function calling, output validation, and memory management, positioning itself as a more structured alternative to direct LLM API calls. Christopher concludes that Sublayer makes “building sophisticated AI agents in Ruby not just possible, but delightful”.

Announcement: Gary Haran shared AI Chat: Run an LLM model from the command line with Ruby, a Ruby script that provides a simple command-line interface for interacting with local LLMs via Ollama.

Article: Can coding agents build complex systems? by Chris Zetter explored the current limitations of AI coding agents in creating complex software systems, asking “can you vibe code a database server?” Chris argues that while AI excels at generating isolated code snippets, it struggles with the architectural decisions and long-term planning required for building substantial applications.

Podcast: Brendan Buckingham and Ryan Frisch from the Rails Business podcast considered Leveraging AI to Enhance User Productivity. The conversation explored building better features with AI in Ruby on Rails applications to benefit users. The episode focused on the future of AI in SaaS, the role of AI in content curation, and how to balance automation with human oversight.

Discussion: The r/rails subreddit discussed CLAUDE.md best practices, focusing on optimizing the CLAUDE.md files that developers use to provide context to AI assistants when working on Rails applications. Suggestions include Ben Sheldon’s Project Guidelines, Claude on Rails, and Agent OS.

Announcement: The Ruby Foundation has announced their 2025 Call for Grant Proposals, specifically seeking libraries for mathematics, science, and engineering. The foundation aims to support projects that extend Ruby's capabilities in these technical domains, with applications closing on October 6th for developers looking to contribute to Ruby's open source ecosystem.

Article: Paul Keen from JetThoughts posited AI Forces What Rails Teams Already Knew: Small Teams Ship Faster. Paul observes that AI forces development teams to confront the reality that “bureaucratic overhead kills velocity more than any technical constraint”. As AI makes “the cost of organizational complexity impossible to ignore”, he concludes that small teams with clear constraints ship better in the age of AI.

Video: Len Epp from Leanpub interviewed Obie Fernandez about his Patterns of Application Development Using AI course. The course includes over two hours of video interviews and focuses on pragmatic patterns like "Multitude of Workers”, "Self-Healing Data”, and "Contextual Content Generation" for integrating large language models into application architectures. The course provides concrete examples and use cases for developers looking to build intelligent, adaptive applications.

Events

Previous

Euroko 2025: Wolfgang Ziegler provided a recap of EuRuKo 2025 - Day 1 and Day 2, featuring talks on Roasting Code for Fun & Profit with Structured AI Workflows by Obie Fernandez, Introducing ReActionView: A new ActionView-Compatible ERB Engine by Marco Roth, Building interactive Ruby gem tutorials with Wasm by Albert Pazderin, RubyLLM: Making AI Development Beautiful Again by Carmine Paolino, and Making Rails AI-Native with the Model Context Protocol by Paweł Strzałkowski. Gapstars also shared some highlights from the event in From Ruby Gems to AI Dreams: Our Euruko 2025 Highlights.

RubyConf India: RubyConf India featured four speakers discussing Ruby and AI, including:

• Deepan Kumar: AI at Runtime: Self Healing Ruby Apps

• Prathamesh Sonpatki: Teaching AI to Debug your Rails Apps (MCP + Observability)

• Vlad Dyachenko: MCP Security: Real World Risks & Defences

• Vishwajeetsingh Desurkar: What if… Ruby Led the AI Revolution?

Upcoming

October 6th - Conference: The Rocky Mountain Ruby Conference on October 6th and 7th in Boulder, Colorado will host two Ruby AI speakers:

• Scott Werner: We Were Voyagers. We Can Voyage Again!

• Christine Seeman: Thoughtful AI for the Rubyist

October 7th - Meetup: Ruby Europe and Paris.rb are joining forces for the Ruby + AI Meetup Paris on October 7th at Algolia in Paris and will include three speakers:

• Chris Hasinski: AI, Offline

• Yorick Jacquin: FastMCP: How to connect AI models to your Ruby applications

• Mariusz Kozieł: Building the future of Ruby through community

October 11th - Conference: XORuby in Portland on October 11th will include a talk by Renée Hendricksen on I know Kung Fu! RubyGems for AI, exploring how to better load the context an AI needs to be successful at a more complex tasks.

October 15th - Meetup: ArtificialRuby is hosting a meetup at Betaworks in New York City on October 15th. If you are interested in presenting at an ArtificialRuby meetup, please fill out this form and let them know. October’s meetup will feature three presentations:

• ​Joel De La Cruz: The New York State RAISE Act: The Race For AI Safety Regulation

• Damani Brown: Giving AI the Keys to Chrome DevTools

• Steve Brudz: Self‑Healing Tests & Everflame Reports: AI‑Powered QA for Rails

October 18th - Workshop: Rails Fever will be hosting another Rails AI event on October 18th in Philadelphia. This interactive session presented by Peter Bailey will explore how AI is reshaping the modern software development lifecycle. Following the presentation covering the landscape of AI-assisted software engineering, there will be a hands-on workshop to build your own AI-enhanced software development automation.

October 18th - Conference: XORuby in San Diego on October 18th will include a talk by Sunjay Armstead titled Never Fear, Unicorns Are Here!, exploring how developers can respond and evolve in the midst of AI’s rapid advancement.

October 25h - Conference: XORuby in Austin, Texas on October 25th will feature a presentation by Landon Gray on Intelligent Event Discovery with Ruby, sharing his experience building an AI-powered event recommendation engine.

November 7th - Conference: RubyWorld Conference 2025 on November 6th and 7th in Matsue, Japan will include three Ruby AI and hardware talks:

• Koichi Ito: Ruby x LLM Ecosystem

• Hayao Kimura: Exploring the World of Electronic Engineering with PicoRuby

• Hitoshi Hasumi: Why Now Is the Right Time for PicoRuby

November 19th - Conference: The San Francisco Ruby Conference on November 19th through the 21st in San Francisco will include an extensive AI program schedule featuring:

• Workshop - Justin Bowen: Building Agents with Rails

• Presentation - Brandon Weaver: Rails Expertise, Distilled: AI Agents That Get Your Monolith

• Presentation - Tia Anderson: Peace, Love, and CRUD: Finding Calm in the Chaos with Ruby, AI, and a Little Garden Magic

• Presentation - José Valim: Navigating Programming Language Evolution in the AI Era

• Presentation - Paweł Strzałkowski: AI Interface in 5 Minutes - Model Context Protocol on Rails

• Presentation - Enrique Carlos Mogollán: The MCP Fog Made Me Do It: A Ruby Inspector's Unexpected Journey

• Keynote - Obie Fernandez: Ruby & AI Conversation

• Roundtable - Edward Kim & Ryan King: CTO Roundtable

• Keynote - Carmine Paolino: RubyLLM: One API, One Person, One Machine for AI

• Presentation - Sarah Mei: The Role of Software Design in an AI World

• Startup Demos - Featuring AI companies Fin AI, Bolt.new, Stepful, Simple AI, Sixfold AI, Cora Computer, Superconductor

• Roundtable - A panel of venture capitalists interested in Ruby and AI-based startups

• Keynote - Vladimir Dementyev: AI-powered Developer Tooling for Rails

Open Source Updates

Code Spotlight

GoldMiner - GoldMiner is a tool from Thoughtbot for finding interesting messages in a Slack channel and turning them into a blog post for the Thoughtbot blog. Uses OpenAI to generate summaries.

New Gems

Links to the RubyGems page, newest releases are first:

moondream - Ruby client for Moondream

neighbor-s3 - Nearest neighbor search for Ruby and S3 Vectors

fast_mcp_jwt_auth - JWT Authorization header authentication for FastMcp RackTransport

fast_mcp_pubsub - PostgreSQL NOTIFY/LISTEN clustering support for FastMcp RackTransport

agentic-commerce-protocol - Type definitions for the Agentic Commerce Protocol specification

numo-optimize - Numo::Optimize provides functions for minimizing objective functions.

rails_ai_agents - A Rails engine for managing AI agents with LLM integration

aider-ruby - Ruby wrapper for aider - AI pair programming tool

rails-agents - Claude Code agents for Rails development

tokenkit - Fast, Rust-backed word-level tokenization for Ruby

numo-linalg-alt - Numo::Linalg Alternative is an alternative to Numo::Linalg.

baml-cc - Unified BoundaryML LLM client

lipdub - Ruby client library for Lipdub.ai API

sdk-reforge - Reforge Launch Ruby Infrastructure

hokipoki-hive-mind - HiveMind: Parasitic Vector Intelligence for Rails

aircana - Humble workflow and context utilities for engineering with agents

ltfi-wsap - LTFI-WSAP Ruby SDK

rails_ai - AI toolkit deeply integrated into Rails applications

google-genai - Unofficial Ruby port of the Python SDK for Google's Gemini API.

New Open Source

Links to the Github repository:

LLM Team - Multi-agent LLM orchestration system that uses specialized AI agents working together through research-critique-synthesis workflows

GeoMCP - An MCP server that aids in geospatial research for cartography projects

Kalmiya - An artificial, intelligent, personal, assistant

Jump Finadvisor Agent - AI-powered assistant for financial advisors

SurvAI - Use Ollama to generate surveys with AI

Google ADK Pattern Implementation Examples - Examples of how to implement Google's Agent Development Kit (ADK) patterns in Ruby tools

RAG Demo Application - Get AI-powered answers to questions about product reviews

Shine - A local CLI agent written in Ruby that can be used for coding and analysis

AI Log Analyzer - CLI that uses OpenAI's API to analyze large log files, extract insights, and answer specific questions about your logs

Devinator - AI assistant that automatically identifies low-complexity bugs and assigns them to Devin for resolution

Konnector Assignment - App that records audio, generates real-time transcriptions, and provides AI-powered summaries

LLM Gateway - Manage multiple local LLM engines with cache, fallback, and external data recovery

AI Receptionist System - Receptionist system that handles incoming phone calls, processes speech, generates intelligent responses, and manages call routing

LinkedIn Post Drafting App - App that transforms raw notes into polished, post-ready LinkedIn content with tone, length, hashtag customization

Probatio Diabolica - A testing framework with large language models (LLMs) in Ruby

AI Social Agent - AI agent to generate developer updates for Reddit and Hacker News

Rubini - CLI AI agent that uses the Google Gemini to deliver an interactive chat to your terminal

CBT Question Generator - Rails application that generates Computer-Based Test (CBT) questions from PDF documents

ai_lint - Have AI review your code

Boo CLI - Terminal assistant that interprets commands in natural language and transforms them into commands for Linux/macOS

ruby_llm_bot - CLI tool to sends questions to a configured LLM, shows a plan and explanation, and optionally executes shell commands with confirmation

Jobs & Opportunities

I’m building a free job matching platform for Rubyists. If you would like to beta test the service, or are an organization searching for Ruby engineers, please reach out at [email protected].

Featured

Remote - Vendis.ai is an AI-powered CRM that creates pipelines from conversations: Senior Ruby on Rails Developer

Remote - Mozilla is a non-profit building open-source tech for internet privacy: Front End Software Engineer, New Products

Remote - KaiPod Learning is a microschool network helping educators start personalized learning communities: Senior Software Engineer

Junior Positions

Remote - 1KOMMA5° is a German renewable energy systems installer and provider: Working Student - Software Engineering Ruby

Remote - iPlayTech is a next-gen iGaming company: Junior Ruby on Rails + Vue

South Africa - nCino is a cloud banking platform for financial institutions: Software Engineer-1

One Last Thing

Anthropic published Effective context engineering for AI agents, a comprehensive guide to optimizing prompt design for autonomous AI systems. Context engineering represents a powerful approach to working with large language models by providing a structured approach to building prompts. As AI can be limited by a model’s restraints and capabilites, this guide helps you ensure the best possible responses by using a carefully crafted set of data and information in your prompts.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.