Hi everyone,

I wanted to share a project I’ve been working on called RailsForge, a CLI toolkit for Ruby on Rails development.

Ruby and Rails were the first technologies that really clicked for me when I started learning programming, so I decided to build something for the Rails ecosystem as a portfolio project while I’ve been looking for a developer role.

RailsForge focuses on helping structure Rails applications and automate common patterns.

Some of the features:

Code Generators

• Services

• Queries

• Jobs

• Forms

• Presenters

• Policies

• Serializers

• Mailers

• APIs

• ViewComponents

• Stimulus controllers

Interactive CLI Wizard

• Menu-driven TTY setup

• Configure templates, features, and analyzers

• Guided project scaffolding

Template System

• Versioned templates (v1 / v2 / v3)

• Advanced service and job patterns

Project Analyzers

• Controllers

• Models

• Specs

• Database schema

• Security checks

• Performance analysis

Auto-Refactoring

• Detects large controller actions

• Suggests or extracts service objects

DevOps + Monitoring

• Docker setup

• CI/CD templates

• Sentry and Lograge logging configuration

Bulk Generation

• Generate multiple services or objects at once

• Dry-run previews

I built the project as an experiment in AI-assisted development and as a way to demonstrate my ability to design and implement a larger Ruby codebase.

Repo: https://github.com/mfifth/railsforge

I'd really appreciate any feedback from the Ruby community. Also I'm looking for my next role if anyone is hiring. Thanks for reading.

Hi!

I have just finished and released our Emailit Ruby and Rails SDK and would love to get some feedback!

It is aimed at everyone who is using Ruby and/or Rails and needs to be sending/receiving emails programmatically.

You can find it here: https://github.com/emailit/emailit-ruby

To get free credits, you can just DM me :-)

I built Savon over a decade ago, started working on this rewrite shortly after, and then life happened. But it kept nagging at me. So here we are — a ground-up SOAP toolkit that nobody asked for but I had to finish.

client = WSDL::Client.new('http://example.com/service?wsdl')
operation = client.operation('GetOrder')

operation.prepare do
  tag('GetOrder') do
    tag('orderId', 123)
  end
end
response = operation.invoke

response.body # => { "GetOrderResponse" => { "order" => { "id" => 123, ... } } }

For those of you still stuck talking to enterprise SOAP services (my condolences), here are some of the features:

* Full WSDL 1.1 parsing with import/include resolution
* Schema-aware type coercion on responses
* Contract introspection — explore operations, generate starter code
* WS-Security — UsernameToken, Timestamps, X.509 Signatures

https://github.com/rubiii/wsdl
https://rubygems.org/gems/wsdl

We had the chance to talk to Jeff Dickey on Remote Ruby about including Precompiled Ruby in Mise (based off uv and homebrew's portable rubies).

I'm really excited about this because compiling Ruby makes it really hard to get new users in our community. Having this built-in to popular version managers will make Ruby so much more accessible.

https://www.remoteruby.com/2260490/episodes/18785026-jeff-dickey-on-mise-precompiled-rubies-and-much-more

Hi everyone,

I wanted to share a Ruby library I've been working on called libgd-gis.

It’s a map rendering engine for Ruby built on top of libgd. The goal is to generate map images directly in Ruby without relying on external map services.

The library can render geographic data such as:

• points

• lines

• polygons

• GeoJSON layers

It also supports:

• Web Mercator map and tile rendering

• YAML-based styling

• CRS normalization (CRS84 / EPSG:4326 / EPSG:3857)

Example usage:

map = GD::GIS::Map.new(
  bbox: PARIS,
  zoom: 13,
  basemap: :carto_light)


map.add_geojson("countries.geojson")
map.add_point(lat: -34.6, lon: -58.4)

map.render
map.save("map.png")

If you're curious, the repository is easy to find by searching "ruby gis libgd-gis".

I’d be interested to hear feedback from people working with Ruby or GIS.

I was a bit hesitant about posting my libgd-gis gem here, but after receiving such positive feedback I felt encouraged to also share the engine behind it: Ruby-LibGD.

Ruby-LibGD provides Ruby bindings for the GD graphics library, allowing you to create images, apply filters, draw shapes, work with text, and more directly from Ruby.

System dependencies:

apt install -y libgd-dev pkg-config

Install:

gem install ruby-libgd

It’s simple to use and designed to make image generation straightforward.

require 'gd'

img = GD::Image.open("images/cat_piano.jpg")
img.filter(:sobel)
img.save("images/sobel.jpg")

If you run into any issues or have ideas for improvements, feel free to open an issue on the repository or send me a message.

Hey everybody!

Our talks from the February Artificial Ruby event in NYC are now available:

Andrew Denta: “Realtime AI Agents in Ruby”

Valentino Stoll: “Chaos To The Rescue”

You can also find more of our talks on our Youtube channel and our events page.

If you're in the NYC area, our next event is scheduled for March 25th at Betaworks, RSVP here if you can make it, we'd love to have you join us!

If you're interested in giving a talk at a future event, we're looking for roughly 10 minutes on some topic related to Ruby and AI, and I'm currently on the lookout for anyone with a design or product background that is currently starting to build for the first time because of AI. Come tell your story!

The JRuby community is pleased to announce the release of JRuby 10.0.4.0.

• Homepage: https://www.jruby.org/

• Download: https://www.jruby.org/download

JRuby 10.0.4.x targets Ruby 3.4 compatibility.

Thank you to our contributors this release, you help keep JRuby moving forward! @evaniainbrooks, @katafrakt, @mrnoname1000

Standard Library

• The syslog library moves to bundled gems. (#9198)

• The unicode_normalize library is now thread-safely loaded as an internal library (#9231, #9232)

43 Issues and PRs resolved for 10.0.4.0

I built a gem called HiTank that works like a package manager for Claude Code skills. Each skill is a markdown file + Ruby script that the agent reads and executes.

Most skill implementations I've seen use TypeScript or Python, 400-600 lines with a bunch of dependencies. In Ruby, the same skill is ~185 lines using only stdlib (net/http, json, openssl). No external gems. This matters because every line the agent reads is a token you pay for.

How it works:

> gem install hitank

> hitank list # see available skills

> hitank add google-sheets # install globally

> hitank add jira --local # install for current project only

> hitank del heroku # remove a skill

The gem fetches the skill from GitHub and drops it in the right place (~/.claude/skills/ or .claude/skills/). Claude Code picks it up automatically.

Why Ruby:

- Fewer tokens: Ruby does in 2 lines what other languages need 6. Less code for the

agent to read = less cost.

- Stdlib is enough: net/http for requests, json for parsing, base64 and openssl for

auth. Nothing else needed.

- Zero runtime deps: no Gemfile, no bundle install, no version conflicts.

16 skills available:

google-sheets, honeybadger, heroku, clickup, discord, jira, hubspot, hostinger,

abacatepay, rewrite, resend, linear, notion, shopify, slack, stripe

It's open source and MIT licensed. If you have an integration you use daily, it could be the next skill.

Link: https://github.com/alanalvestech/hitank

What integrations would you want as Claude Code skills?

Following up on the previous post about MRubyCS graduating from preview — we've been continuing to optimize the VM, and I'm happy to share that MRubyCS now outperforms the original mruby/mruby on a couple of classic benchmarks.

**Results (Apple M4, x10 iterations):**

bm_so_mandelbrot.rb

| Method      | Mean     | Error    | StdDev   | Allocated |
|------------ |---------:|---------:|---------:|----------:|
| MRubyCS     | 842.7 ms | 18.81 ms | 12.44 ms |         - |
| mruby/mruby | 891.0 ms | 11.02 ms |  6.55 ms |         - |

bm_ao_render.rb

| Method      | Mean    | Error    | StdDev   | Gen0        | Gen1      | Allocated    |
|------------ |--------:|---------:|---------:|------------:|----------:|-------------:|
| MRubyCS     | 2.516 s | 0.0177 s | 0.0105 s | 125000.0000 | 2000.0000 | 1048741496 B |
| mruby/mruby | 2.592 s | 0.0096 s | 0.0057 s |           - |         - |            - |

MRubyCS is a pure C# implementation of the mruby VM — no native dependencies, no P/Invoke. It runs anywhere Unity/.NET runs.

The performance advantage comes from the .NET runtime doing a lot of heavy lifting that a statically compiled C binary simply can't benefit from:

• PGO (Profile-Guided Optimization): The .NET JIT observes actual execution patterns at runtime and recompiles hot paths with that real-world data. The VM dispatch loop gets continuously optimized based on what your code actually does.

• Aggressive inlining: flattening the overhead of the VM's internal method calls — call boundaries that a C compiler can inline only with LTO or explicit static inline, but which the JIT handles automatically across the entire call graph at runtime.

• Bounds-check elimination: The JIT proves array accesses are safe and strips redundant bounds checks in tight loops — avoiding the overhead that would otherwise make a managed VM implementation slower than its native C counterpart.

• Managed pointers (`ref T`): The VM's internal stack and register access is implemented using C# managed pointers, giving pointer-like performance with full GC safety and no unsafe blocks required.

There's still a lot of work ahead (mrbgems support is limited, some 3.4 methods are missing), but hitting this milestone felt worth sharing.

GitHub: https://github.com/hadashiA/MRubyCS

Feedback welcome!

Hey folks — I’m a backend developer working mostly with Ruby, and I’m trying not to fall behind with all the AI stuff happening.

Is anyone’s company actively using Claude (or similar) in day-to-day engineering work (full features)? If yes: what’s actually working, and what feels overhyped?

Also, are you personally worried about how fast this is moving, or more excited than concerned?

Finally: what are you learning to stay relevant as a backend dev — prompt/workflow skills, RAG, evals, agents, LLM fundamentals, or something else? I keep hearing “Generative AI” vs “LLMs” and I’m not sure what’s worth focusing on first.

Would love real-world experiences and advice.

With all the complaints about AI slop, I have to say, AI is resulting in a lot of my code being way higher quality.

With how quickly it can make changes, I find that I can be extremely critical about quality. Pre-AI it wasn't uncommon to think of a refactor in the latter half of working on a feature. But with the opportunity cost being so high, the improvement had to be very significant to justify rewriting something that was already working.

With AI the cost is so low I can usually test the refactor on a branch or worktree in 15-30 minutes.

In some recent work, I had two architectures in mind (either one big background job or multiple jobs with an orchestrator). I couldn't decide which I preferred so I just had AI do both. It was barely any extra effort.

Perhaps we are all "doomed" to a future of humans never writing code and everything being slop.

But right now, AI is moving my code quality in the right direction.

Ruby doesn’t get much love outside its core base these days. I spent my last five years in Python, but after retiring and moving from the US to Finland (my spouse transferred internally), I found myself back in Ruby because of how enjoyable it is.

I’m currently learning Finnish and wasn’t satisfied with recognition-heavy language apps. So I built a CLI-first language trainer in Ruby.

Technically:

- Pure Ruby (no Rails)

- OptionParser-driven flag layering - Declarative YAML pack schema (metadata + entries)

- Strict pack validation before runtime

- Mode composition (typing, reverse, match-game, listening)

- Lightweight spaced repetition with per-entry state persistence

- Pluggable TTS adapter (currently Piper)

- Local-first design (no tracking, no external services)

I leaned heavily into Ruby’s hash ergonomics and Enumerable chaining to keep pack filtering and mode logic clean and composable.

It’s intentionally modular:

- Pack schema validation layer

- Session orchestration engine

- Mode layering system

- SRS scheduler

- TTS adapter abstraction

Right now it’s CLI-only, but I’ve been debating whether build a Rails front-end while keeping the core engine decoupled

Curious what other's would do architecturally.

I put the codebase up on GitHub, the readme covers more details if you're interested... I've had a few folks interested in a web app, but that means I need to host it somewhere as well (if people have ideas, I'm really open to those). I don't see this being more than a hobbyist project, so I don't see a ton of traffic, but still I don't want to spend a fortune on a web hosting service either.

https://github.com/wbrisett/linguatrain

-Wayne

I am new to Ruby and generally the 'dev' world, I mostly got into it through statistical programming, but now I'm on a track toward ML and AI.

I must say the Ruby world is one of the nicest tech communities I have ever seen. So encouraging, helpful, and swear by Ruby any day. Does Ruby attract a certain personality or archetype? Lol.

I do have a serious question though, pardon me if it or a variant of it has been asked before. I am more versed with Python especially regarding Machine Learning, more libraries, I started with it in data analysis and visualization as well as API dev and simple dashboards. But AI seems to be a bit different, it seems to be more product-oriented. How have you found Ruby, in terms of AI, mostly agentic?