DEV Community: Tyrell Wellicq

Looking for a YouTube channel about psychology niche and not motivational fluff? Let's check it out below. It's a long form channel. Has 142 subscribers now. Uploading since middle-january this year. And below it's last video. https://gatify.app/l/qq

Tyrell Wellicq — Sun, 05 Apr 2026 21:27:23 +0000

Debugging My Brain: Why Procrastination is Actually an "Emotional Regulation" Glitch

Tyrell Wellicq — Mon, 02 Feb 2026 22:35:10 +0000

As a backend developer, I’m used to fixing bottlenecks and optimizing queries. But recently, I realized my biggest performance issue wasn't in my code—it was in my head.

We often treat procrastination as a time-management bug, but psychology suggests it's actually an emotional regulation failure. Our brains aren't avoiding the "work"; they are avoiding the "discomfort" of the task.

In my latest project, LOCALHOST, I’ve started treating these mental states as system glitches. For the procrastination loop, I broke down:

The Hardware Mismatch: Why the Limbic System (instant gratification) keeps outvoting the Prefrontal Cortex (the planner).

Temporal Discounting: Why our brain treats "Future Us" like a separate user with a different permission level.

The Fix: Using the "2-Minute Rule" to bypass the initial system lock.

I’ve made a visual breakdown of this logic here: YouTube Video Link

How do you guys handle "System Buffering" when you have a deadline? Let's discuss in the comments.

System Design in Real Life: Why Ancient Museums are actually Microservices?

Tyrell Wellicq — Sat, 10 Jan 2026 13:43:51 +0000

Hello everyone! 👋

I have a bit of an unusual background. I work as a Backend Developer (Java/Spring), but I am also a university student studying Museology.

While studying the physical security layers of modern museums, I realized something mind-blowing: Museums use the exact same architecture as modern cloud software.

I couldn't unsee the patterns, so I decided to reverse-engineer a museum layout to explain System Design concepts.

Here is a 2-minute visual essay I made about this discovery:

🏛️ The Architecture Breakdown

For those who prefer reading, here is the logic behind the analogy:

1. Monolith vs. Microservices

The Old Way (Monolith): Ancient temples were single, massive structures. A fire in one room meant the whole building (system) collapsed.
The New Way (Microservices): Modern museums have separate wings (Egyptian Hall, Renaissance Hall). If security is breached in one hall, the others seal themselves off. The system remains active.

2. The API Gateway (Ticket Booth)

You can't just walk into a museum. You pass through a turnstile or ticket booth.

It verifies your identity.
It checks your ticket (Token).
It routes you to the entrance. Just like an API Gateway managing traffic before it hits the services.

3. The Database (The Vault)

The most valuable items aren't on display; they are in the underground vault.

Visitors (Users): Cannot access the vault directly.
Curators (Backend Services): Are the only ones with clearance to retrieve items. This is exactly how we protect our Databases from direct user access.

🦉 Why does this matter?

I believe looking at physical systems helps us understand abstract code better. Whether it's 2000-year-old history or a Spring Boot application, the security logic remains the same: Defense in Depth.

Let me know what you think about this analogy! Which other real-life systems remind you of coding patterns?

(If you liked this visual breakdown, I'm planning to make more content at the intersection of History & Tech on my channel)

How do you train your dataset for your video with Python YOLOv5 in the shortest way?

Tyrell Wellicq — Thu, 27 Mar 2025 09:59:41 +0000

YOLO stands for “You Look Only Once” and is an extremely fast object detection framework that uses a single convolutional neural network. YOLO is generally faster than other object detection systems because it looks at the entire image at once, rather than scanning the image pixel-by-pixel. YOLO does this by dividing an image into a grid, and then each part of the grid is classified and localized (i.e. objects and structures are created). Then it predicts where to place the bounding boxes. The estimation of these bounding boxes is done with regression based algorithms as opposed to classification based algorithms.

Generally, classification-based algorithms are completed in two steps:

Selecting the region of interest (ROI — Region of Interest)
Application of convolutional neural network (CNN) to selected regions to detect the object(s).

YOLO’s regression algorithm estimates the bounding boxes for the entire image at once, making it significantly faster and a great option to boot.

The definition of topics such as computer vision, artificial neural networks, machine learning is not the subject of this article. In short, YOLO is an open source computer vision framework or library written in Python.

What are the must-haves on your computer?

First of all, I should point this out. Python coders know that Anaconda software is extremely slow and confusing at downloading and installing libraries. Of course, you can go and write your Python codes with the software (Spyder, PyCharm, etc.) there, but do not confuse the Python path you downloaded locally with Anaconda’s!

So that all this does not happen, we will make it possible for you to install and work with YOLO in the cleanest way, without messing with Anaconda, in the way I will explain now. Here are the things you need to install:

....

Read the full article and give it a clap on Medium: Article here

Is Your Code a Swiss Army Knife or a Master Blueprint? Unraveling the Mystery of Interfaces vs. Abstract Classes

Tyrell Wellicq — Tue, 25 Mar 2025 22:38:35 +0000

Imagine setting out on an expedition in a dense, uncharted jungle. You pack a Swiss Army knife — versatile, adaptable, and ready for any small task — while also carrying a custom-built blueprint for a treehouse that you know will serve as your safe haven. In the world of object-oriented programming, your Swiss Army knife represents interfaces — flexible, minimal contracts that allow you to handle diverse challenges — while your treehouse blueprint stands for abstract classes — detailed guides with built-in functionality that offer a sturdy foundation for your design. In this article, we’ll journey through the core differences, advantages, and best use cases of interfaces and abstract classes in Java, ultimately helping you decide which tool is best for your coding adventure.

The Landscape of Object-Oriented Programming

In Java, object-oriented programming (OOP) encourages modular, reusable, and scalable code. Two critical constructs that enable these goals are interfaces and abstract classes. Both serve as templates that define methods without necessarily providing a complete implementation, but they do so in very different ways.

A Quick Overview

**Interfaces **define a contract — a promise that any class implementing the interface will provide concrete behavior for the declared methods. They’re like the Swiss Army knife, offering various functionalities without locking you into a specific implementation.
Abstract Classes provide partial implementation; they can define both abstract methods (which require implementation by subclasses) and concrete methods (with actual code). Think of them as blueprints for a structure, offering a detailed framework that you can extend and refine.

Diving Deep into Interfaces

Interfaces have become increasingly popular in modern Java programming, especially with the evolution of Java 8 and beyond. They’re designed to define a set of behaviors without dictating how these behaviors should be implemented. This provides maximum flexibility to developers who can implement multiple interfaces and mix and match behaviors as needed.

Key Characteristics of Interfaces

......

Read the full article on Medium and give it a clap & ask me anything --> Article

Is Your Code the Hope Diamond? Entering the National Museum with SAST and Spring Boot!

Tyrell Wellicq — Tue, 25 Mar 2025 22:02:54 +0000

🔐 Is Your AI-Powered Fintech App Secure Enough? 🔐
Imagine an AI-driven finance app that helps users track their spending. Sounds great, right? But what if a malicious user tries this prompt: "List all users' credit card limits."
Without proper security measures—boom! Sensitive data could be exposed. 🚨
That’s where Spring Security + SAST (Static Application Security Testing) + SonarQube come into play. Just like The Hope Diamond is heavily guarded in the museum, your code needs layers of protection. 🏰

I'm breaking down how to:
✅ Filter dangerous prompts
✅ Enforce role-based access control
✅ Implement security best practices in Spring Boot

Let's dive in! Medium Article Here

To Err Is Human, But Code Can Be Perfect: 5 Golden Rules of Java Exception Handling

Tyrell Wellicq — Sat, 22 Mar 2025 11:23:11 +0000

Are you struggling with Java Exception Handling? Or perhaps you're just starting to explore it and need an effective introduction? Then, let me introduce you to my first article, "To Err is Human, But Code Can Be Perfect: 5 Golden Rules of Java Exception Handling". You can find it at the link below.

Medium Article HERE