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Open Source vs. Closed Source Software

Kevin Ly — Wed, 06 Aug 2025 02:46:20 +0000

In today’s fast-evolving tech landscape, the debate between open source and closed source software continues to spark interest — and for good reason. Whether you're a developer, tech enthusiast, startup founder, or simply a curious user, understanding the difference between these two approaches is essential.

In this blog, we’ll explore what open source and closed source software really are, compare their pros and cons, and discuss notable examples — including the controversial case of OpenAI, which started as an open source initiative.

What is Open Source Software?

Open source software (OSS) is software whose source code is made available to the public. Anyone can inspect, modify, and enhance it. This model promotes transparency, collaboration, and community-driven development so which is why it attracts many programmers around the world to an open-source project.

Examples include:

Linux – the foundation of many operating systems and servers.
VS Code – a free, powerful code editor maintained by Microsoft.
Firefox – the open-source web browser by Mozilla.
TensorFlow – an open-source machine learning framework developed by Google.

Most OSS projects are hosted on platforms like GitHub or GitLab and licensed under terms like MIT, GPL, or Apache to define how the code can be used or modified.

What is Closed Source Software?

Closed-source software, on the other hand, is proprietary software whose source code is kept secret. Only the original creators — typically companies — can legally view or alter the code.

Examples include:

Microsoft Windows
macOS
Adobe Photoshop
OpenAI’s GPT models (as of today)

Users of closed-source tools can access the software’s features, but not the internal code that powers it. If you're trying to access the closed-source software, you might face some serious legal penalties.

So... Which Should You Choose for Your Project?

Let’s say you’re building something.
A passion project. A startup. A game. A tool.
Should you go open source… or closed?

Here’s how to think about it:

✅ Choose Open Source if:

You want to build in public, attract contributors, and grow a community.
You value transparency, especially for tools used by other developers.
You’re creating something educational, experimental, or mission-driven.
You want to earn trust quickly — especially in fields like security or infrastructure.

Or… you simply believe in the philosophy:

“Code should be open, for everyone.”

🔐 Choose Closed Source if:

You're building a product you plan to monetize or license.
You need to protect intellectual property or competitive advantages.
You want full control over features, branding, and distribution.
You have legal or security obligations to keep the code private.

Or you’re targeting an audience that doesn’t care how the sausage is made — just that it works.

Still not sure?

Many companies today actually choose a hybrid model:

They open-source parts of their infrastructure to build trust and adoption.
But they keep the core proprietary to sustain the business.

Think of it this way:

Open source is a great way to build reach. Closed source is a great way to build revenue. And in some cases, you can do both.

So instead of asking “Which is better?”
Maybe the better question is:

“What kind of relationship do I want with my users?”

The OpenAI Controversy: From Open to Closed

One of the most fascinating case studies is OpenAI.

Founded in 2015 as a non-profit research organization, OpenAI's mission was to ensure that artificial general intelligence (AGI) benefits all of humanity. It pledged to make research and code open source — as stated in its founding charter.

In its early years, OpenAI released models like GPT-2 and tools like OpenAI Gym openly. However, in 2020, OpenAI made a pivotal shift. It withheld GPT-3’s code and full model weights, citing concerns over misuse. Later, OpenAI became a “capped-profit” company and began monetizing its models through APIs and partnerships (notably with Microsoft).

“We were wrong to think we could release these powerful models openly without seeing harmful use,” said OpenAI CEO Sam Altman.

Today, OpenAI’s latest models (like GPT-4) are entirely closed source, and even the training data remains secret. This has sparked ongoing debate about transparency, ethics, and the future of AI research.

Conclusion

The open vs. closed source debate isn't just technical — it's philosophical. It's about who gets to innovate, who controls the tools we use, and how we shape the future of technology.

As users and developers, it’s important to stay informed, make conscious choices, and support initiatives that align with your values.

And as OpenAI’s shift shows us, the line between open and closed isn't always fixed — it evolves with power, progress, and responsibility.

Not Everyone Gets Into FAANG — and That’s Okay

Ethan Carter — Fri, 18 Jul 2025 14:51:02 +0000

When I first started learning how to code, I knew very little about the tech industry.

All I knew was that “FAANG” — Facebook, Amazon, Apple, Netflix, and Google — was where the best engineers ended up. They were the dream. The goal. The finish line.

I saw the job titles, the salaries, the stories of engineers who made it there at 19 or 20.
It felt impossible and inspiring at the same time.
And slowly, without realizing it, I began tying my own worth to that destination.

“If I don’t get into FAANG, am I even good enough?”
“If others can do it, why can’t I?”
“What’s wrong with me?”

I never said these questions out loud. But they were always there, quietly eating away at my confidence.

The Hidden Pressure We Don’t Talk About

Let’s be honest: FAANG has become more than just a collection of companies.

In our industry, it’s almost a status symbol.
Like a badge of honor, you wear to prove you’ve “made it.”

And because of that, we rarely question it. We just chase it.

We spend months grinding Leetcode, memorizing system design patterns, and reading interview guides.
We spend so much time trying to fit into the mold that we forget to ask ourselves:

“Do I even want this for the right reasons?”
“Or am I just afraid of falling behind?”

Yes, and that is my case.

My FAANG Story (Or... Lack of One)

I applied to multiple FAANG companies, more than once.
Sometimes I got ignored. Sometimes I made it to the final round, only to be told “no.”

Each rejection hit harder than the last.
Not because I lost the opportunity, but because I felt like I had lost my identity as a capable developer.

“If I’m not good enough for FAANG, maybe I’m just not good enough, period.”

It sounds irrational now. But back then, it felt real.
That’s the problem with one-size-fits-all success stories — they leave no room for people who are still figuring things out or for people who choose to take a different route entirely.

What I Learned From Not Getting In

In the beginning, I saw FAANG as the only path to validation.
But being rejected forced me to ask a harder question:

“If not FAANG, then what?”
“What else is out there — and could that also be meaningful?”

I started working on side projects on things that I love.
I made new friends.
I helped build tools that real people used, even if it wasn't at scale.

And slowly, something changed.

I realized that the joy of being a developer doesn’t come from where you work.
It comes from what you build.
From who you build it for.
From the tiny wins, the deep learnings, the hard lessons, and the late nights where something finally “clicks.”

The Truth About FAANG (That We Rarely Say Out Loud)

FAANG is not evil.
It’s full of talented engineers, incredible projects, and big opportunities.
If you get in — congratulations, you deserve it.

But we need to stop pretending that it’s the only path worth celebrating.
Because here’s the truth that I learned from a lot of people around me:

Not everyone gets into FAANG.
Many brilliant people don’t.
Some never apply. Some never get past the first round.
And some realize… they don’t even want it anymore.

And that’s okay.

Redefining What “Making It” Means

In the end, we all have to decide for ourselves what success looks like.

Is it a job title?
A company name?
A six-figure salary?

Or is it something quieter?

Waking up excited to work on a problem you care about
Sitting down for dinner with your family after a long day of work
Laughing with friends on a Friday night, not thinking about code for once

None of these show up on LinkedIn headlines.
But they matter.
Sometimes more than you think.

If You’re Still Trying To “Make It” — Read This

Maybe you’re applying. Maybe you’ve been rejected.
Maybe you’re burnt out from the grind.
Or maybe you’ve already decided that you’re done chasing FAANG.

Wherever you are, you’re not alone.
And you are not less than anyone.

You don’t need a big name behind you to do meaningful work.
You don’t need a fancy offer to call yourself a real developer.
You don’t need validation from a company to believe in your craft.

You’re already enough.
And your story is just beginning.

Final Words

Not everyone gets into FAANG — and that’s okay.
What matters isn’t where you work.
It’s what you’re building, who you’re becoming, and how you choose to grow.

How to Structure a React Project in 2025: Clean, Scalable, and Practical

Nathan Chung — Fri, 13 Jun 2025 01:37:00 +0000

How should you organize a React project?

Have you ever asked yourself that question when starting a new React app? Whether it’s a tiny side project or a big production app, I’m pretty sure we’ve all wondered: “What’s the best way to structure this so it looks clean and scales well later?”

Well, here’s the truth: There’s no official standard. Since React is just a library, not a full-blown framework, it doesn’t force you into any specific folder structure or project layout.

That’s why in this post, I’ll be sharing what’s worked for me, based on personal experience and a lot of research. Hopefully, it’ll give you a solid starting point to organize your own React projects in a clean and scalable way.

🧠 The Philosophy: Structure Based on Scale

First, let me clarify this:

A React project should be structured based on the size of the app and its complexity. The bigger the project, the more important it becomes to separate concerns, reuse logic, and isolate features.

So, here’s a general structure I recommend for most small-to-medium React projects, with explanations for each folder:

src/
├── assets/
├── components/
├── pages/
├── routes/
├── hooks/
├── services/
├── utils/
├── contexts/
├── styles/
├── App.jsx
├── main.jsx

Let’s go through each of them.

📁 `assets/` – Static Files & Media

This folder contains static resources such as:

Images
Fonts
Icons
Global SCSS/CSS files

Use this for anything that doesn't contain logic, just visual or media assets.

assets/
├── images/
├── fonts/
├── styles/

📁 `components/` – Shared UI Components

This is for reusable components like buttons, modals, inputs, etc., that are used across multiple parts of your app.

components/
├── Button/
│ ├── Button.jsx
│ └── Button.module.css
├── Modal/
│ ├── Modal.jsx
│ └── Modal.module.css

📁 `pages/` – Route-Level Components

Each file here corresponds to a route in your app. Think of it as the screen-level UI.

This helps separate page layout logic from reusable UI pieces.

pages/
├── Home.jsx
├── Login.jsx
├── PostDetail.jsx

📁 `routes/` – Routing Configuration

All your route definitions and React Router setup can live here. It makes routing centralized and easy to update when your app grows.

routes/
├── AppRoutes.jsx
└── PrivateRoute.jsx

📁 `hooks/` – Custom Hooks

If you create your own hooks (which you will!), this is where they live:

hooks/
├── useAuth.js
├── useToggle.js

Tips:

Keep reusable logic here
Prefix them with use to follow React convention

📁 `services/` – External API Logic

Anything related to API calls, database interactions, or third-party integrations goes here. This way, your components stay clean and declarative.

services/
├── api.js
├── postService.js
└── authService.js

📁 `utils/` – Utility Functions

Helper functions that don't belong to a specific feature.

utils/
├── formatDate.js
├── validateEmail.js

Tips:

Keep logic centralized
Avoid duplication across features

📁 `contexts/` - React Context Providers

If you're using React Context API for global state or shared configurations (like theme, auth status, or language settings), it's a good idea to organize them in their own folder.

Each context file typically includes:

The createContext() call
A context provider component
Any relevant logic or default values

contexts/
├── AuthContext.jsx
├── ThemeContext.jsx

📁 `styles/` - Global Styling & Theme Config

While individual component styles can live in Button.module.css or *.scss, this folder is perfect for your global CSS setup, such as:

Tailwind or SCSS config
Theme variables
Reset or normalize files

styles/
├── global.css
├── variables.css
├── tailwind.config.js

📄 `App.jsx` & `main.jsx` – Entry Points

App.jsx is your main application shell (where routes, providers, and layout go). Example: Vite + React

import { useState } from 'react'
import reactLogo from './assets/react.svg'
import viteLogo from '/vite.svg'
import './App.css'

function App() {
  const [count, setCount] = useState(0)

  return (
    <>
      <div>
        <a href="https://vite.dev" target="_blank">
          <img src={viteLogo} className="logo" alt="Vite logo" />
        </a>
        <a href="https://react.dev" target="_blank">
          <img src={reactLogo} className="logo react" alt="React logo" />
        </a>
      </div>
      <h1>Vite + React</h1>
      <div className="card">
        <button onClick={() => setCount((count) => count + 1)}>
          count is {count}
        </button>
        <p>
          Edit <code>src/App.jsx</code> and save to test HMR
        </p>
      </div>
      <p className="read-the-docs">
        Click on the Vite and React logos to learn more
      </p>
    </>
  )
}

export default App

main.jsx is the actual root file where React is rendered to the Document Object Model. Example: Vite + React

import { StrictMode } from 'react'
import { createRoot } from 'react-dom/client'
import './index.css'
import App from './App.jsx'

createRoot(document.getElementById('root')).render(
  <StrictMode>
    <App />
  </StrictMode>,
)

🚀 As Your Project Grows...

When things scale even further (teams, business complexity, domains), you can transition to a feature-sliced or domain-driven structure:

src/
├── entities/      // business models like User, Post
├── features/      // login, comment, create post
├── shared/        // shared components, hooks, utils
├── widgets/       // composed UI units (e.g., Header, Sidebar)
├── pages/
├── processes/     // flows (e.g., sign-in flow)

This is inspired by Feature-Sliced Design. Check it out here: https://feature-sliced.design/docs

🧩 Final Thoughts

React gives you freedom, but with freedom comes responsibility.
If you don’t plan your project structure early, you’ll face chaos later.

Start small and flat.
Then, organize by features.
Eventually, evolve into a modular, domain-based architecture.

Whatever the size of your app, the goal is the same:
Readable, maintainable, and scalable code.

JavaScript vs TypeScript in 2025: What You Should Learn

Ethan Carter — Fri, 06 Jun 2025 00:02:34 +0000

If you're stepping into the world of web development in 2025, there's a high chance you've been torn between learning JavaScript or TypeScript. This debate isn’t new, but the context around it has evolved significantly in recent years.

In this article, we’ll break down the key differences, current trends, and practical advice to help you decide which language to invest your time in this year.

🔍 The Basics: What Are JavaScript and TypeScript?

JavaScript (JS)

JavaScript is the most widely-used language for web development. It runs in every browser, powers nearly every interactive website, and is supported by an ocean of libraries, frameworks, and tools.

TypeScript (TS)

TypeScript is a superset of JavaScript developed by Microsoft. It adds static typing, interfaces, and compile-time error checking—all while eventually compiling back into JavaScript.

All TypeScript is JavaScript, but not all JavaScript is TypeScript.

🌐 2025 Trends: What's Changed?

In 2025, the landscape of frontend and backend development will continue to shift:

TypeScript adoption has become mainstream.
Tooling and framework support is TypeScript-first.
AI-assisted coding (like Copilot and ChatGPT plugins) works smoother with TypeScript.
More jobs demand TypeScript.

⚖️ JavaScript vs TypeScript: Key Comparisons

Feature	JavaScript	TypeScript
Typing	Dynamically typed	Statically typed
Learning Curve	Easier for beginners	Slightly steeper
Error Handling	Runtime errors only	Compile-time + runtime errors
Tooling	Good	Excellent
Maintainability	Medium	High
Framework Support	Full	Full (often better DX)
Community Size	Huge	Large and growing fast
Performance	Same	Same (compiles to JS)

🧠 When Should You Learn JavaScript?

JavaScript is still essential knowledge. You should start with JavaScript if:

You're just starting out and want to understand the fundamentals.
You're building small projects or scripts.
You want to dive into frontend frameworks like React or Vue.
You’re into creative coding (p5.js, Three.js, etc.)

✅ Recommendation: Learn the core concepts of JavaScript first — variables, functions, async/await, scope, etc.

🚀 When Should You Learn TypeScript?

TypeScript shines when:

You're working on larger codebases.
You want scalability and fewer bugs.
You’re building apps with Next.js, Deno, or Node.js.
You're aiming to be a professional developer.

✅ Recommendation: Once you're comfortable with JavaScript, learn TypeScript early. The benefits grow fast.

🔄 Learning Path in 2025: A Smart Roadmap

Start with Vanilla JavaScript: Learn syntax, ES6+, DOM, fetch, async/await.
Build Projects: Start with some simple projects first.
Refactor with TypeScript: Add TS to one of your JS projects.
Use TS in Frameworks: Built with Next.js (TypeScript) or SvelteKit.
Join a Team or OSS: Collaborate on real-world TypeScript codebases.

💼 What Do Employers Want in 2025?

Startups: JavaScript is often enough if you're fast.
Companies: Mid-large companies prefer TypeScript for scale.
Open Source / Tech Leads: Favor TypeScript for long-term maintenance.

🧩 Final Verdict: JavaScript or TypeScript?

Don’t choose one over the other—embrace both.

Learn JavaScript first to build your foundation.
Learn TypeScript next to build your future.

In 2025, TypeScript isn’t replacing JavaScript. It’s enhancing it.

💬 Let's Discuss

Are you team JS or TS in 2025?

What’s your biggest struggle while learning either?

Drop your thoughts or questions below—let’s grow together. 🚀

🧠 Extra Resources

If you found this article helpful, give it a ❤️ or share it with someone starting their dev journey in 2025!

Should You Learn to Code or Pursue a CS Career in 2025? A Wake-Up Call for the AI Era

Kevin Ly — Mon, 02 Jun 2025 20:52:23 +0000

It's 2025

You’ve just graduated with a Computer Science degree — or maybe you're self-taught, having put in countless hours on LeetCode, bootcamps, and personal projects. You believed in the dream: that tech is the future, that software engineers are in demand, that maybe you’d build the next big thing.

But now?

Layoffs are everywhere.
AI writes code.
Even “entry-level” jobs want 3+ years of experience.

And you're left wondering:

“Did I mess up? Should I have even learned to code?”

If you’re feeling confused, frustrated, or just uncertain, you're not alone. Many people are struggling to find a job right now, even if that is an internship or entry-level, and if they do find work, they’re not sure what AI will do or improve tomorrow, as layoffs show no signs of abating.

Let’s take a step back, breathe, and figure out what’s really going on and how we can move forward with clarity, purpose, and confidence.

🕰️ A Look Back: When Machines Replaced Humans… or Did They?

Let’s rewind to the 19th century.

Back then, skilled textile workers in England and the U.S. — tailors, seamstresses, weavers — made clothes by hand. Their work required talent, precision, and years of practice.

And then what? The Industrial Revolution.

The invention of mechanized looms could do in minutes what took humans hours. Fear swept through the workforce. Jobs were at risk. The Luddites even smashed machines in protest.

Sound familiar? It should — because it's the same narrative we hear today from tech CEOs, news articles, and podcasts. AI is advancing rapidly, they say. It’s reshaping industries, automating tasks, and yes, replacing jobs. In tech, especially, new grads now find themselves competing not just with each other but also with recently laid-off employees from big tech and alumni from top-tier universities. The pressure is real.

If we compare today’s AI boom with the Industrial Revolution of the 19th century, the pattern is strikingly similar. Machines are once again taking over tasks once done by humans, and we’re living through a new kind of revolution.

So, what does history teach us?

Those who resisted change were left behind.
Those who adapted — who learned to work with the new tools — found opportunity.

Back then, traditional roles like tailors and weavers didn’t disappear overnight, but they evolved. The people who embraced sewing machines and learned to work with looms didn’t lose their value — they shifted their skills into a new form.

🧭 Start With Purpose: What Is Ikigai?

So, what is Ikigai?

Because when everything around you feels shaky — trends, headlines, maybe even your confidence — you need something solid to guide you.

That something is Ikigai (生き甲斐) — a Japanese concept that means “a reason for being.”
It lives at the intersection of:

❤️ What you love
✅ What you're good at
🌍 What the world needs
💵 What you can be paid for

If you’re feeling lost on your CS journey, this is a great place to start.

Ikigai isn’t just about finding a job — it’s about building a meaningful life.

Ask yourself:

Question	Your Thoughts
Do I enjoy building things, solving problems, and making ideas real?	...
Can I get better at it, even if it’s hard now?	...
Can this skill help real people or solve real problems?	...
Are there paths where I can earn from this eventually?	...

If your gut says yes, then don’t quit. Let AI be your co-pilot. Let rejections build resilience. Let the community, like us, lift you.

But if your gut says no, that’s okay too. You’re not a failure. You’re just refining your direction. Not everyone needs to be a coder.

But everyone needs a calling.

💡 So... Should You Still Learn to Code?

Let’s be real:

Right now, AI is evolving so quickly that we can't predict exactly what tomorrow will bring. One thing is certain, though: we have to adapt to the changes shaping the tech industry. But beyond technical skills, there’s something else we need to build — and that’s trust.

In a world where tools like InterviewCoder — built by Roy Lee, a former Columbia student — can help people cheat in their technical interviews, or where AI can assist someone in earning a degree without truly understanding a single line of code, trust becomes more valuable than ever.

So if you're genuinely passionate about programming or if coding aligns with your Ikigai, keep learning. Keep building. Show your projects on GitHub. There's still space for you in tech. But if you're here just for the money? Then it's time for a reality check — because this journey isn’t as glamorous as some YouTubers make it seem.

Because the truth is:

The future belongs to those who collaborate with AI, not fear it.
The job market will reward those with grit and curiosity, not just certificates.
The world still needs builders, dreamers, and problem solvers.

“The machine might know the syntax — but only you know the soul behind the software.”

So, should you learn to code or pursue a CS career in 2025? If it’s your purpose or passion, then yes.

Amazon: From Online Bookstore to Tech Empire

Calvin Park — Sat, 17 May 2025 22:23:24 +0000

Chapter 1: The Birth of a Visionary (Pre-1994)

The early 1990s were a time of tectonic shifts in both politics and technology. The Cold War had just ended, giving way to a wave of globalization. Meanwhile, the internet, once a military and academic curiosity, was on the verge of becoming commercially viable. In 1990, Tim Berners-Lee introduced the World Wide Web, and by 1993, web browsers like Mosaic were making the internet accessible to the average user.

Amid this digital dawn, a Wall Street executive named Jeff Bezos was working at D.E. Shaw, a prestigious hedge fund. Bezos, a Princeton graduate with a background in computer science and electrical engineering, came across a stat that changed everything: internet usage was growing at 2,300% per year.

Bezos immediately recognized the commercial potential of the web. He drafted a list of 20 product categories that could be sold online. Books stood out—they were standardized, easy to ship, and had a vast catalog. In 1994, Bezos left his lucrative job, packed his car, and drove to Seattle with his wife, MacKenzie, to start a company. He called it "Cadabra," but quickly changed it to "Amazon" after the world's largest river, symbolizing the company he hoped to build.

Chapter 2: Garage Dreams (1994–1995)

Amazon was founded in July 1994 in Bezos' garage. The vision was clear: create an "everything store," starting with books. Seattle was chosen not only for its tech talent but also because it was close to Ingram, a major book distributor.

Bezos and his small team built the website by hand. On July 16, 1995, Amazon.com went live. The first book ever sold? Fluid Concepts and Creative Analogies by Douglas Hofstadter. Within 30 days, they were selling books in all 50 states and 45 countries. The site was a hit. Customers were drawn to the convenience and the vast selection.

From the start, Bezos instilled a customer-obsessed culture. He would bring an empty chair into meetings to represent the customer. It was his way of reminding employees who they were working for.

Chapter 3: Get Big Fast (1996–1999)

As the internet gold rush gained momentum, Amazon raised millions in venture capital and went public in 1997 at $18 per share. Bezos was laser-focused on growth over profit. His famous mantra: "Get Big Fast."

Amazon expanded into music, videos, toys, electronics, and more. It introduced features like customer reviews, personalized recommendations, and 1-Click ordering, which would become e-commerce standards.

In 1999, Time Magazine named Jeff Bezos Person of the Year, recognizing Amazon as a leader in the internet revolution. But storm clouds were gathering.

Chapter 4: The Crash That Didn’t Kill (2000–2002)

The dot-com bubble burst in 2000. Tech stocks crashed, and many internet startups went bankrupt. Amazon's stock plummeted from over $100 to under $10. Analysts predicted its demise.

But Bezos stayed the course. He made difficult decisions: layoffs, cost-cutting, and a renewed focus on operational efficiency. He introduced Amazon Marketplace in 2000, allowing third-party sellers to list products on the platform—a decision that would prove genius.

While others folded, Amazon survived. By 2002, it posted its first quarterly profit. The company had weathered the storm and emerged stronger.

Chapter 5: Prime Time (2003–2005)

To further differentiate itself, Amazon doubled down on logistics. It built cutting-edge fulfillment centers and began experimenting with faster shipping.

In 2005, Amazon launched Amazon Prime: for $79 a year, members received unlimited two-day shipping. This was a turning point. Prime increased customer loyalty and lifetime value, and it would eventually include streaming video, music, and more.

This period laid the groundwork for Amazon's transformation from an online retailer to a platform with an ecosystem.

Chapter 6: The Cloud Beneath It All (2006–2010)

Behind the scenes, Amazon had been building robust infrastructure to power its growing retail empire. In 2006, it began offering this infrastructure to other companies through Amazon Web Services (AWS). The first offerings were S3 (Simple Storage Service) and EC2 (Elastic Compute Cloud).

AWS was a silent revolution. It allowed startups and enterprises to rent computing power instead of buying expensive servers. Companies like Netflix, Airbnb, and Dropbox built their businesses on AWS.

By 2010, AWS had become a multi-billion-dollar business, quietly making Amazon the backbone of the modern internet.

Chapter 7: Kindle, Alexa, and Smart Everything (2007–2014)

In 2007, Amazon disrupted publishing with the Kindle, its e-reader that made books digital and portable. It wasn’t just a gadget; it was a new business model that cut out publishers.

Amazon followed with the Fire tablet, Fire TV, and in 2014, the Echo and Alexa. Alexa brought voice assistants into the home, launching a new era of ambient computing.

These innovations kept Amazon in consumers' homes, not just on their screens.

Chapter 8: The Everything Company (2015–2020)

Amazon went on a shopping spree. It acquired Whole Foods in 2017, signaling its serious move into groceries. It expanded Amazon Go cashier-less stores, invested in AI, logistics, healthcare, and more.

Amazon Studios grew into a serious competitor to Netflix, winning Emmys and Oscars. AWS became the market leader in cloud computing. The company surpassed $1 trillion in market value.

Jeff Bezos became the world’s richest man, symbolizing Amazon’s transformation from scrappy startup to dominant force.

Chapter 9: Changing of the Guard (2021–Present)

In 2021, Bezos stepped down as CEO, handing the reins to Andy Jassy, the head of AWS. The world was emerging from the COVID-19 pandemic, during which Amazon played a crucial role in delivering essential goods.

Amazon now faces new challenges: antitrust scrutiny, unionization efforts, climate concerns, and competition from other tech giants.

Still, it remains a leader in AI, robotics, logistics, and cloud computing. From retail to healthcare to entertainment, Amazon touches nearly every facet of modern life.

Chapter 10: The Legacy of Day 1

Jeff Bezos often talks about "Day 1" — the idea that Amazon must always act like a startup, with hunger, speed, and customer obsession. In his final shareholder letter, he warned of "Day 2": stasis, irrelevance, and decline.

Today, Amazon continues to innovate, pushing into space (via Blue Origin), artificial intelligence, and sustainability. The company started with a simple idea in a garage and evolved into a global infrastructure powering commerce, cloud computing, and content.

The story of Amazon is not just about a company. It’s about how technology, vision, and relentless execution can reshape the world.

And it’s still only Day 1.

The Psychology of Programming: Why Naming, Readability & Simplicity Matter

Alvin Jaime — Wed, 23 Apr 2025 19:46:06 +0000

Understanding the human brain is as important as understanding the machine. Clean code isn’t just good for compilers—it’s good for people.

Programming isn’t just about making computers do things—it's about communicating with other humans through code. As systems grow, teams expand, and requirements evolve, the clarity and maintainability of code become far more important than the initial cleverness of an implementation.

In this post, we’ll explore the psychology of programming through the lens of Cognitive Load Theory—a psychological framework that helps explain why naming, readability, and simplicity aren't just nice-to-haves but essentials for writing great software. We'll explore practical strategies to reduce mental overhead for yourself and others, backed by timeless wisdom from programming legends like Donald Knuth and Martin Fowler.

What Is Cognitive Load Theory?

Cognitive Load Theory (CLT) is a framework from educational psychology developed by John Sweller. It suggests that the human brain has a limited amount of working memory available at any given time, and the way we design tasks (or, in our case, code) should aim to reduce unnecessary mental effort.

There are three types of cognitive load:

Intrinsic Load – The inherent difficulty of the task.
Extraneous Load – The unnecessary complexity in the way the task is presented.
Germane Load – The effort required to construct schemas (mental models).

In programming, we want to minimize extraneous load and manage intrinsic load, so developers can focus on solving the actual problems (germane load) instead of deciphering convoluted code.

Why Naming Matters

“There are only two hard things in Computer Science: cache invalidation and naming things.” – Phil Karlton

The Brain's Struggle With Ambiguity

The names you give to variables, functions, and classes are the primary interface your code has with the reader. When a developer reads calculate() vs. calculateMonthlyInterest(), they engage a very different level of mental parsing.

Poor naming creates extraneous load—forcing developers to guess what something does, interrupting flow, and increasing chances of mistakes.

Naming Tips:

Be specific: userList is better than list1.
Avoid noise words: Instead of dataManagerHelper, just use DataProcessor if that's what it is.
Follow conventions: Be consistent with casing, prefixes, suffixes, and pluralization across your codebase.

Why Readability Matters

“Programs must be written for people to read, and only incidentally for machines to execute.” – Harold Abelson, SICP

The Reading-to-Writing Ratio

Studies (like those cited by Steve McConnell in Code Complete) show that developers spend 10x more time reading code than writing it. This means that the primary audience for your code is not the computer—it's the future human (often you) who has to understand and modify it.

Readability Tips:

Use whitespace wisely: Group related logic visually.
Limit function size: Aim for short, focused functions—ideally under 20-30 lines.
Comment why, not what: If the why isn’t obvious, explain it; don’t just restate what the code already shows.
Use meaningful structure: Break large files into logical modules or classes.

Why Simplicity Matters

“Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” – Martin Fowler
“The real problem is that programmers have spent far too much time worrying about efficiency in the wrong places and at the wrong times.” – Donald Knuth

The Hidden Cost of Cleverness

Trying to outsmart the reader with a single-line regex hack or terse bitwise manipulation might save you a few keystrokes today, but it could cost hours of debugging down the road.

Knuth’s quote reminds us that premature optimization is the enemy. Code is read far more often than it is executed. Optimization should never come at the expense of clarity unless there's a measured, proven performance benefit.

Simplicity Tips:

Avoid deep nesting: Use early returns to simplify flow.
Prefer composition over inheritance: Especially in large OOP systems.
Don’t over-engineer: Use design patterns when they help, not just because they exist.
Be boring: Simple, predictable code is easier to test and maintain.

How to Apply This in Practice

Here are some concrete steps you can take to embrace these principles in your daily work:

Use Code Reviews for Teaching
Use reviews to share reasoning behind naming choices and refactoring for readability. Encourage discussions around clarity, not just functionality.
Read Code Regularly
Study open-source codebases, your team’s older code, or even your own past work. Notice what’s easy to understand and what isn’t. Reverse-engineering your own code after six months is a humbling and enlightening experience.
Embrace Linters and Formatters
Tools like Prettier, ESLint, Pylint, or Black enforce consistent formatting, freeing up mental energy for higher-level problems.
Refactor Ruthlessly
Refactoring isn’t a luxury—it’s part of your job. If a function grows too large or confusing, break it down. Make small, frequent improvements as part of your development process.

Conclusion

Writing clean code is about empathy. When you write understandable, well-named, and simple code, you’re showing kindness to your teammates, your future self, and your users.

Programming is not just logic—it's language. It’s art and science. The code you write today will either reduce or increase cognitive load for those who come after you.

“Simplicity is the soul of efficiency.” – Austin Freeman

So name with care. Read with empathy. And keep your code as clear as your intentions.

Further Reading

Clean Code by Robert C. Martin
Code Complete by Steve McConnell
The Pragmatic Programmer by Andy Hunt and Dave Thomas
Refactoring by Martin Fowler
Structure and Interpretation of Computer Programs by Harold Abelson and Gerald Jay Sussman

Web Development: What is that?

Kevin Ly — Sat, 15 Feb 2025 04:14:01 +0000

These days, it's hard to imagine life without our devices—phones, computers, or iPads. They help us relax after a long day and assist us with countless tasks. One thing that we are all familiar with from the moment we first touched a computer until now is a web browser, most typically Microsoft's Internet Explorer, and Google Chrome. Web browsers help us access a larger world online by giving us access to all kinds of web applications from social media to daily newspaper applications. But have you ever stopped to wonder what a "web application" really is and how it works? In today's blog post, I'll break down how a web application works and the key elements that make up an application.

What is a web application?

A website or web application can be understood as a collection of web pages containing information, including images, articles, music, or anything else that the website creator wants to put up. For example, when accessing the Amazon website, we will see web pages such as the home page, product page, category page, and cart page. These web pages are typically accessible via the Internet and can be viewed using a web browser such as Google Chrome, Firefox, Safari, or Edge.

How does a web application work?

How a web application works can be summarized as follows:

After accessing the web browser via the Internet, the user will start typing on the URL bar above to go to a desired website. After the user presses Enter, the browser will find the place where the website is being stored (which we call the server). To find the server, first, our web browser will contact something called a DNS Server to find the IP address of that website by translating the website name we just entered in the URL bar, such as www.example.com, into a series of numbers called an IP address, such as 192.168.1.1.

After getting that IP address, which means we get the address of the server, our browser will send a request (or we often know it as HTTP requests) to the server where the website's data information is being stored and request the specific data that the user wants to access.

After the server receives the browser's request, it will respond to the browser with the status (whether it was successful or not) and the requested data.

Finally, when the browser receives a response from the server stating that it has been successful, it will start rendering the page.

Imagine this process as looking up a friend's phone number in a phonebook. You know the friend's name (the website address), but you need their phone number (the IP address) to call them. The DNS Server acts like the phonebook's lookup service and the IP address is like the phone number you need to dial to reach your friend.

What exactly is the term “Web Development”?

Web development is the process of creating websites and applications for
the Internet. It encompasses various aspects, including web design, web
content development, client-side/server-side scripting, and network security configuration. Web development can be divided into two main categories: Front-End and Back-End.

Front-End Development:
Front-end development is all about what you see and interact with on a website. Think of it as the "face" of the website. Here are the three basic parts that all website front ends must have:

HTML: HTML is like the skeleton of a webpage. It gives structure to the site, laying out where everything goes. Imagine the web application is like a house, HTML is like the wall, bricks, and everything that builds the house but we're not painting it yet. Every element on the page, like headings, paragraphs, and images, is defined using HTML.
CSS: CSS is what makes the website look good. It’s like the paint, furniture, and decorations you add to your house to make it stylish and comfortable. CSS lets you change colors, fonts, spacing, and layout to make everything look just right. Without CSS, websites would look plain and boring.
Javascript: JavaScript brings the website to life. It’s the magic that makes things move and respond when you click, type, or scroll. Think of it as the electrical wiring and plumbing in a house, making sure everything works smoothly and interactively. With JavaScript, you can create cool features like slideshows, form validations, and interactive maps.

Back-End Development:
Back-end development focuses on the server side of web applications. It involves managing databases, server logic, and application programming interfaces (APIs). Key components include:

Server: The server is a powerful computer that hosts websites and web applications. It handles requests from the client's browser and processes them. Servers can be set up using various technologies such as Node.js, Python (Django, Flask), Ruby on Rails, Java, and PHP.
Database: A database stores and manages the data used by a website or web application. Common databases include MySQL, PostgreSQL, MongoDB, and SQLite. Databases are crucial for storing user information, content, and other dynamic data.
API (Application Programming Interfaces): APIs allow different software systems to communicate with each other. In web development, APIs enable the front end to interact with the back end. They facilitate data exchange and functionality between the client and server.

Conclusion

In terms of "Web Development", we still have a lot of things to discuss in advance like responsive design, package management, front-end and back-end framework, database, and a lot of other things but by understanding these key elements, we can appreciate the complexity and intricacies involved in creating and maintaining websites. Web development requires a blend of creativity, technical skills, and problem-solving abilities to build functional and visually appealing web experiences.

Additional:
This blog post has been transformed into a video on our AlgoSync YouTube channel to reach a wider audience and share knowledge more broadly.

Link: Video's link

DEV Community: AlgoSync

Open Source vs. Closed Source Software

What is Open Source Software?

What is Closed Source Software?

So... Which Should You Choose for Your Project?

The OpenAI Controversy: From Open to Closed

Conclusion

Not Everyone Gets Into FAANG — and That’s Okay

The Hidden Pressure We Don’t Talk About

My FAANG Story (Or... Lack of One)

What I Learned From Not Getting In

The Truth About FAANG (That We Rarely Say Out Loud)

Redefining What “Making It” Means

If You’re Still Trying To “Make It” — Read This

Final Words

How to Structure a React Project in 2025: Clean, Scalable, and Practical

🧠 The Philosophy: Structure Based on Scale

📁 assets/ – Static Files & Media

📁 components/ – Shared UI Components

📁 pages/ – Route-Level Components

📁 routes/ – Routing Configuration

📁 hooks/ – Custom Hooks

📁 services/ – External API Logic

📁 utils/ – Utility Functions

📁 contexts/ - React Context Providers

📁 styles/ - Global Styling & Theme Config

📄 App.jsx & main.jsx – Entry Points

🚀 As Your Project Grows...

🧩 Final Thoughts

JavaScript vs TypeScript in 2025: What You Should Learn

🔍 The Basics: What Are JavaScript and TypeScript?

🌐 2025 Trends: What's Changed?

⚖️ JavaScript vs TypeScript: Key Comparisons

🧠 When Should You Learn JavaScript?

🚀 When Should You Learn TypeScript?

🔄 Learning Path in 2025: A Smart Roadmap

💼 What Do Employers Want in 2025?

🧩 Final Verdict: JavaScript or TypeScript?

💬 Let's Discuss

🧠 Extra Resources

Should You Learn to Code or Pursue a CS Career in 2025? A Wake-Up Call for the AI Era

🕰️ A Look Back: When Machines Replaced Humans… or Did They?

🧭 Start With Purpose: What Is Ikigai?

💡 So... Should You Still Learn to Code?

Amazon: From Online Bookstore to Tech Empire

Chapter 1: The Birth of a Visionary (Pre-1994)

Chapter 2: Garage Dreams (1994–1995)

Chapter 3: Get Big Fast (1996–1999)

Chapter 4: The Crash That Didn’t Kill (2000–2002)

Chapter 5: Prime Time (2003–2005)

Chapter 6: The Cloud Beneath It All (2006–2010)

Chapter 7: Kindle, Alexa, and Smart Everything (2007–2014)

Chapter 8: The Everything Company (2015–2020)

Chapter 9: Changing of the Guard (2021–Present)

Chapter 10: The Legacy of Day 1

The Psychology of Programming: Why Naming, Readability & Simplicity Matter

What Is Cognitive Load Theory?

Why Naming Matters

Why Readability Matters

Why Simplicity Matters

How to Apply This in Practice

Conclusion

Web Development: What is that?

What is a web application?

How does a web application work?

What exactly is the term “Web Development”?

Conclusion

📁 `assets/` – Static Files & Media

📁 `components/` – Shared UI Components

📁 `pages/` – Route-Level Components

📁 `routes/` – Routing Configuration

📁 `hooks/` – Custom Hooks

📁 `services/` – External API Logic

📁 `utils/` – Utility Functions

📁 `contexts/` - React Context Providers

📁 `styles/` - Global Styling & Theme Config

📄 `App.jsx` & `main.jsx` – Entry Points