The Biased Symptom: Choosing the Right Tool Over the Comfortable One

The Biased Symptom: Choosing the Right Tool Over the Comfortable One

Sleek v2.0 public release is here

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What has changed in our latest release?

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All new features available for all public channel users

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Coding collaboration with over 200 users at once

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Real-time code save every 0.1 seconds

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Through the years, I’ve worked with a lot of technologies. Sometimes I didn’t evaluate them properly; sometimes I went deep. What I’ve noticed, though, is that many developers stick to one technology and never look beyond it. That can be dangerous, and it’s what I call “the biased symptom.”

My Journey Across Technologies

Like many developers, I started coding in my teenage years with PHP - back when the backend handled the frontend, and jQuery sprinkled some glitter on top.

At 22, I joined a small Drupal boutique, where most of my time was spent on Drupal. Later, I moved into Python for three years, then JavaScript for four, and now I’m back in the Python world. Along the way, I dabbled in Golang, picked up some Java for my (never-finished) B.Sc., and explored other tools. In short, I’ve wandered around enough to see patterns repeat.

What Is the Biased Symptom?

The biased symptom happens when we choose a technology not because it’s the best fit, but because it’s familiar.

It shows up in startups all the time. Before LLMs, you’d probably reach for Python or Node.js, React or Angular, and start coding yourself to death. Today, it’s even easier to just accept GPT’s output as gospel and roll with whatever stack it spits out.

But when the project grows, reality sets in:

  • CI/CD pipelines need to be configured

  • Data migrations become painful

  • A forgotten field in the user schema forces a rewrite

This is when the biased symptom hurts the most; because what felt easy at the start becomes expensive to maintain.

Laravel as an Example

Take Laravel. Many developers dismiss PHP as “old” or “not scalable,” but Laravel provides:

  • An artisan CLI to generate boilerplate code

  • Built-in migrations and modularity

  • livewire and blade for modern frontend work

  • A wide official ecosystem such as laravel cloud and nightwatch

  • First-class testing tools (and Pest v4 is excellent)

These features save time compared to cobbling together equivalents in other stacks. Yet, people overlook Laravel because of outdated assumptions about PHP:

  • “PHP is old.” So is Git.

  • “PHP doesn’t scale.” Neither does poorly written Python.

  • “PHP isn’t evolving.” Heard of the arrow operator?

The point isn’t that Laravel is the answer to everything. The point is that dismissing it without evaluation is biased in action.

A Real Client Story

I recently worked with a client who thought they needed a CMS. Naturally, my Drupal reflex kicked in - after all, I know Drupal inside and out. It would have been easy to spin up a project and relive my high-school coding days.

But here’s the catch: the client’s team was Python-based. Introducing PHP into their stack would have added complexity and long-term friction.

So I stopped. I MVP’ed alternative solutions. And when I presented the options to the team leader, his response shifted everything:

“A few months ago, Drupal might have made sense. Today, our technical team will own this project.”

That was the turning point. We pivoted back to FastAPI and React.

The result? An internal infrastructure project with:

  • React components built using atomic design and Ant Design abstractions

  • Types generated from backend APIs via OpenAPI/Swagger

  • Tight TypeScript integration to give developers confidence

  • CI/CD pipelines and Storybook for smooth collaboration

Drupal wasn’t the wrong tool in general - but it was the wrong tool here. Avoiding the biased symptom saved us from long-term headaches.

Takeaways

After 15 years in code, here’s what I’ve learned about avoiding the biased symptom:

  1. Pause before committing - Don’t rush into the tool you know best. Stop, drop, and roll back to basics.

  2. Accept outside input - If the right tool isn’t in your toolbox, lean on vendors, libraries, or even AI-assisted research to find a better fit.

  3. Separate fit from comfort - Great technologies become nightmares when used in the wrong context.

Failure is the most valuable currency - if you learn from it. Choosing the right tool, not the familiar one, is how you avoid paying too high a price.

Photo Credit: designer491/Bigstock.com

About the author

Storyteller, technical challenge-solver, semi-pro photographer, crème brûlée enthusiast, and software engineer .Roy has been developing since 2011 and believes he can make your dreams come true - given just enough time.Over the years, he has collaborated with big names like Harvard University, and his open-source contributions have reached organizations such as the White House, the European Union, and the Drupal community. Roy enjoys speaking at meetups and firmly believes that crafting a clean, thoughtful frontend is every bit as important as patching a critical CVE.