Ruby, AI, and the Product Engineer: Bringing the Ruby Community Conference back to SeQura

In March 2026, SeQura sponsored Ruby Community Conference Winter 2026 in Kraków. More than 200 Rubyists gathered for a day of talks, workshops, and plenty of hallway conversations. One of my favorite parts of these events is catching up with people I haven’t seen since the last conference and hearing what other teams are building.

At SeQura, we also have a small tradition: if you attend a conference, you come back and share the most interesting ideas with the rest of the team. This year, that wasn’t difficult because almost every conversation eventually found its way back to AI.

The Rise of the Product Engineer

One talk that stuck with me was Obie Fernandez’s keynote on AI and the future of software development.

His main argument was that AI is changing what it means to be a software engineer. As coding assistants become better at generating boilerplate and solving routine tasks, the value of engineers shifts away from typing code and toward understanding problems, making product decisions, and exercising good judgment.

Obie described this evolution as the rise of the “Product Engineer” — someone who combines technical skills with a strong understanding of the business and the user.

Whether or not you agree with every prediction, it’s hard to ignore the direction things are moving. The most valuable engineers won’t necessarily be the ones who write the most code, but the ones who can identify the right problems to solve.

That idea felt very familiar. At SeQura, AI is already helping us spend less time on repetitive work and more time on building products. A good example is sq-platform-buddy, an internal AI assistant created by our Platform team that helps answer infrastructure-related questions and guides engineers through self-service processes. The goal isn’t to replace engineers; it’s to remove friction.

Why Ruby Fits So Well with AI

Another talk I enjoyed was Carmine Paolino’s presentation on Ruby and AI.

Carmine, the creator of ruby-llm, made the case that Ruby remains one of the most productive languages for building AI-powered applications. While many AI examples online are written in Python, Ruby’s focus on developer happiness, readability, and rapid iteration makes it a great fit for integrating LLMs into real products.

This is something we’ve experienced firsthand at SeQura.

Within our Merchant Portal, we use AI to help merchants better understand their business performance. Instead of presenting only raw financial data, we use ruby-llm to generate summaries and insights based on information already available in our systems. The goal is not to replace dashboards, but to make the information easier to understand and act upon.

Building While the Industry Changes

What I took away from Kraków wasn’t that AI will replace software engineers or that every application suddenly needs an LLM.

What stood out was how quickly AI is becoming a normal part of the software development toolbox. The conversations have shifted from experimentation to practical adoption: where AI creates value, where it doesn’t, and how teams can use it responsibly.

Many of the ideas discussed on stage felt surprisingly close to what we’re already exploring at SeQura. From internal developer tooling to merchant-facing features, we’re continuously looking for ways to use AI where it genuinely improves the experience for engineers and customers.

Conferences are often about discovering what’s next. This year, Kraków felt a little different. Many of the ideas being discussed weren’t future predictions anymore — they were things people are already building today.

And that’s probably what made the event so interesting.

If building pragmatic AI tools in Ruby sounds exciting to you, we are always looking for Product Engineers. Check out our open roles at SeQura.