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The Philosophy in Practice: The GitLab Model of Accelerated Iteration ​

Looking at theory is one thing, but seeing how it works in real life is what truly convinces us, right? The idea that choosing "boring" helps with speed sounds good on paper, but GitLab is living proof that this yields massive results when applied for real. They make no secret of it: the fact that they managed to make 106 releases in 106 consecutive months comes directly from this commitment to "boring solutions".

Complexity Limits Speed ​

GitLab's logic is simple and straightforward: the speed at which we innovate is held back by the complexity we let accumulate. Every new technology, every extra layer or dependency we put into the system brings weight. Over time, this weight slows down the entire organization. To avoid falling into this trap, they actively choose the simplest and most predictable path. It is this discipline of steering clear of the complicated that has allowed GitLab to continue delivering fast even after growing for more than ten years.

Sometimes, these decisions even seem strange to those seeking technical perfection, because they prioritize delivering value early instead of polishing the elegance of the code. Ultimately, what matters most?

Practical Examples of "Boring" ​

To understand how this culture works in practice, the best way is to look at examples where they preferred to use what they already had at hand instead of reinventing the wheel:

  • Leveraging Existing Features: When they needed to create issue boards—something quite complex—one might imagine they would build a new system from scratch. But no. They used the existing label system to build the lists. This allowed them to deliver the feature very quickly, using pieces that everyone already knew and knew how to maintain.
  • Avoiding Unnecessary User Interfaces (UI): They needed a way to authenticate with Vault. Instead of spending time creating a new UI or a CLI, they opted to use a JSON Web Token and simply documented how to use curl with the API endpoints. Problem solved with almost zero development and maintenance effort. Smart, isn't it?
  • The Simplest Tool Possible: One of the most famous cases was the critical migration from Azure to GCP. A project of this size usually calls for expensive project management software. Do you know what they used? A simple checklist inside a GitLab issue. Even with 140 changes along the way, the process was transparent and everyone knew what to do. They resisted the temptation to overcomplicate and used what was familiar to everyone.
  • Disciplined Incrementalism: There was a time when they wanted to keep an issue's title visible while the user scrolled the page. The idea was to pin just the title, but they soon realized that the MVP also needed to show the issue's state. The key point here is that they stopped there. They didn't try to change the entire navigation or apply this to every corner of the system. They delivered the bare minimum that already helped the user, keeping total focus on iteration.

"Boring" is Not a Dogma, It's a Strategy ​

What GitLab teaches us is that choosing "boring" is not a rigid rule for the rest of your life. It is a strategic decision based on context. In the beginning, they used tools like Gitolite because it worked and let the team focus on what mattered. When the company grew and the context changed, they switched.

This shows that being "boring" is not a flaw. It is choosing the simplest tool, one that brings less weight and lets us be fast now, without taking away our flexibility to change later if needed.

Deep down, this philosophy is about respecting the human being behind the code. We know how complex tech stacks fry the brain and drain focus. Remember that story about the MiG-15 pilot's fatigue? It is the same mental exhaustion we feel when dealing with unpredictable technologies. Having a stable environment is what allows the team to work calmly.

When the stack is predictable and we trust it, it becomes much easier to enter a "flow state." Instead of spending energy worrying about the infrastructure, we focus all our creativity on solving the customer's problem. It is stopping the fight with the "how" to focus on the "what."

Now that we have seen how "boring" accelerates value delivery, let's explore a movement that seems to be taking us in the opposite direction: AI. How do these new technologies converse with a philosophy that puts simplicity and stability first?