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Islam Gagiev
Islam Gagiev
longreads /

Building a resilient AI Client in Ruby with Stoplight and Ruby_LLM

Calling external AI providers (like OpenAI, Gemini, or Claude) is a common task in modern web applications. However, these services can sometimes be slow, return errors, or become completely unavailable. This can lead to cascading failures that bring your entire application down. To prevent this, you can use the Circuit Breaker pattern, which isolates failing services and even allows for a graceful failover to a backup provider. In Ruby, the stoplight gem provides a straightforward way to implement this pattern and build a resilient client, in this article we will use it with ruby_llm to handle AI providers. To see this implementation in action and explore the details, be sure to check out the repository containing the code examples used in this article.
Read more Building a resilient AI Client in Ruby with Stoplight and Ruby_LLM
Alexey Solilin
Alexey Solilin
longreads /

CSS Scroll Snap for Overflow Elements

Creating smooth, native-feeling horizontal tab navigation is essential for modern web applications. CSS Scroll Snap provides an elegant solution that ensures your tabs feel polished and intuitive across all devices, with special attention to mobile touch interactions.

Alexey Solilin
Alexey Solilin
longreads /

Async Modal on Rails with Native <dialog> Element

In this post, I'll show you how to create asynchronous modal windows in Rails using Turbo Frames and the native <dialog> element. This approach combines the power of Rails' Hotwire stack with modern web standards to create smooth, accessible modal experiences without heavy JavaScript frameworks. We'll build a complete example using a login form that loads dynamically and displays in a native dialog with proper focus management and backdrop handling.

Natalie Kaminski
Natalie Kaminski
longreads /

Are AI Coding Assistants Saving Developers Time or Creating Technical Debt?

Over the past several months, our engineering team has been running structured experiments with AI coding assistants like Claude, Copilot, and others across real projects.
The goal was simple: understand where these tools truly add value, and where they fall short.
The results? A mix of magic, frustration, and important lessons for anyone serious about building long-term, maintainable software.
Natalie Kaminski
Natalie Kaminski
longreads /

Why Ruby on Rails Is the Best Stack for Vibe Coding in the Age of AI

The concept of vibe coding is picking up momentum.

For those unfamiliar, vibe coding is a collaborative, human-in-the-loop development approach where large language models (LLMs) handle the heavy lifting of code generation based on natural language prompts. As a developer, you describe what you want, and the AI takes care of writing, adjusting, and even debugging code. You’re no longer bogged down by boilerplate or fiddling with syntax. Instead, you’re shaping the architecture, guiding the logic, and focusing on the why of what you’re building, not just the how.

It’s an exciting shift. But here’s what’s not being talked about enough:
Vibe coding only works as well as the stack you’re using.
And in my experience, across countless projects, dozens of teams, and many languages, Ruby on Rails outperforms the rest when it comes to this new way of building software.

Let’s talk about why.

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