DEV Community: Kelvin Kariuki

How to use public-apis: A collective list of free APIs

Kelvin Kariuki — Sun, 21 Jun 2026 17:53:02 +0000

If you've ever dreamt of building a project but felt limited by not having your own data or backend, then public APIs are your superpower. They unlock a universe of data and functionality, allowing you to prototype, learn, and build real applications without writing a single line of server-side code (initially, at least).

Discovering Your API Playground: The `public-apis` Repository

The internet is teeming with free, publicly accessible APIs, but finding a reliable, well-documented one can be like searching for a needle in a haystack. Enter public-apis, a phenomenal GitHub repository that curates an extensive, categorized list of free APIs for use in software and web development.

This repository is an absolute goldmine for developers of all levels. Whether you're a beginner looking for a simple API to fetch random facts, or an experienced developer needing data for a sophisticated prototype, public-apis has something for you. It's meticulously maintained, regularly updated, and offers a quick overview of each API's key characteristics, such as authentication requirements, HTTPS support, and CORS status.

Navigating the Treasure Trove

When you land on the public-apis GitHub page, you'll immediately notice its well-structured README.md. APIs are categorized into dozens of topics, ranging from "Animals" and "Anime" to "Development" and "Finance."

Each entry in the list typically includes:

API: The name of the API.
Description: A brief explanation of what the API does.
Auth: Specifies the authentication method (e.g., No, API Key, OAuth).
HTTPS: Indicates if the API supports secure HTTPS connections (always prefer Yes).
CORS: Shows if the API supports Cross-Origin Resource Sharing (Yes is crucial for client-side JavaScript applications).
Link: A direct URL to the API's homepage or documentation.

This structured format allows you to quickly scan and identify APIs that meet your project's technical requirements and data needs.

Choosing Your First Public API: Key Considerations

Before diving into code, let's look at what makes a good candidate for your first public API, especially for learning or prototyping:

Authentication (Auth):
- No: Ideal for beginners. You can hit the endpoint directly without needing keys or complex OAuth flows.
- API Key: Requires you to sign up for a key. This key is often passed as a query

Master Programming by Recreating Your Favorite Technologies From Scratch

Kelvin Kariuki — Sun, 21 Jun 2026 17:40:45 +0000

Master Programming by Recreating Your Favorite Technologies From Scratch

Do you ever wonder what truly happens under the hood of the tools you use daily? Building your own version of established technologies isn't just a fun coding challenge; it's a direct path to profound understanding, transforming you into a more capable and confident developer.

The "Build-Your-Own-X" (BYOX) Philosophy: Unlocking Deeper Understanding

We developers spend a lot of time using abstractions. Frameworks, libraries, and managed services simplify our lives, but they can also create a gap in our foundational knowledge. The "Build-Your-Own-X" (BYOX) philosophy bridges this gap. It's about taking a familiar piece of technology – be it a web server, a command-line tool, a small ORM, or even a mini database – and attempting to recreate its core functionality from scratch.

This isn't about replacing Nginx or PostgreSQL; it's about dissecting them, understanding their fundamental principles, and implementing those principles yourself. The benefits are immense:

Profound Understanding: You'll grasp the why and how of design choices, data structures, and algorithms in a way tutorials can't teach.
Enhanced Debugging Skills: When you understand the layers beneath your code, diagnosing complex issues becomes significantly easier.
Improved System Design: Deconstructing existing systems gives you a blueprint for building robust, scalable applications.
Problem-Solving Prowess: You'll learn to break down seemingly insurmountable challenges into manageable parts.
Career Advancement: Interviewers love candidates who can speak to the fundamentals and show initiative beyond typical framework usage.

Choosing Your "X": Start Small, Think Big

The key to a successful BYOX project is choosing the right "X."

Developer take on: Code duplication is far cheaper than the wrong abstraction (2016)

Kelvin Kariuki — Sun, 21 Jun 2026 17:28:14 +0000

When building software, developers often face a foundational dilemma: embrace the "Don't Repeat Yourself" (DRY) principle fiercely, or tolerate a degree of duplication for clarity and flexibility. While DRY is a cornerstone of good design, blindly pursuing it can lead to a far more insidious and costly problem: the wrong abstraction.

This article, inspired by a timeless debate, dives into why allowing some strategic duplication can be a superior, more pragmatic path than prematurely abstracting code that isn't ready for it.

The Allure of Abstraction

As developers, we're taught to seek elegance, efficiency, and reusability. Abstraction promises a world where common logic is encapsulated, bugs are fixed in one place, and features are built upon stable, well-defined interfaces. The desire to create a perfect, generic solution that anticipates every future use case is strong, almost innate. We dream of frameworks and libraries that solve problems universally.

This drive is often commendable, but it carries a hidden danger. Just as premature optimization can be the root of all evil, premature abstraction can be the silent killer of project agility and maintainability.

The Heavy Toll of the Wrong Abstraction

What happens when we abstract too early, or in the wrong way?

Increased Complexity: Abstractions are meant to simplify, but a bad one adds layers of indirection. Instead of understanding a

Developer take on: (How to Write a (Lisp) Interpreter (In Python)) (2010)

Kelvin Kariuki — Sun, 21 Jun 2026 17:18:25 +0000

Developer Take On: How to Write a (Lisp) Interpreter (In Python) (2010 Edition, Revisited)

Understanding how programming languages work under the hood is one of the most powerful insights a developer can gain. Building a Lisp interpreter in Python, a classic project from around 2010, remains an unparalleled journey into the core mechanics of compilation and execution, deepening your appreciation for the tools you use every day.

Remember those foundational projects that circulate among developers, like Peter Norvig's famous "How to Write a (Lisp) Interpreter (in Python)"? That piece of wisdom, and many like it from that era, demystified language creation using the elegant simplicity of Lisp's S-expressions and Python's readability. While the year 2010 might seem a digital eternity ago, the principles of interpreter design are timeless. Let's revisit this classic challenge with a modern developer's perspective, focusing on the practical steps and enduring lessons.

The Interpreter's Anatomy: A Three-Act Play

At its heart, any interpreter follows a fundamental structure, often broken down into a few key stages:

Lexical Analysis (Lexing/Tokenization): The raw source code, a string of characters, is broken down into a stream of meaningful "tokens." Think of these as the individual words and punctuation marks of the language.
Syntactic Analysis (Parsing): The stream of tokens is then structured into a hierarchical representation, typically an Abstract Syntax Tree (AST). This tree reflects the grammatical structure and relationships within the code.
Evaluation (Execution): The AST is traversed, and the operations described by its nodes are performed in the correct order, producing a result.

For Lisp, this process is famously simplified by its uniform syntax: everything is an S-expression (Symbolic Expression). This means lists of items enclosed in parentheses, where the first item is often a function or operator, and the rest are its arguments.

Act 1: The Lexer – Breaking Down the Walls of Text

The first step is to turn our Lisp source code, like (+ 10 (* 2 5)), into a list of atomic units.
'(', '+', '10', '(', '*', '2', '5', ')', ')'

Python

Developer take on: Code duplication is far cheaper than the wrong abstraction

Kelvin Kariuki — Sun, 21 Jun 2026 17:04:18 +0000

Developer take on: Code duplication is far cheaper than the wrong abstraction

Every developer is taught to "Don't Repeat Yourself" (DRY), and for good reason. Yet, an overzealous pursuit of DRY can lead us down a path of over-engineering, creating complex abstractions that are far more costly than a little deliberate duplication. This article challenges the dogma of pure

Developer Take on: Code Duplication Is Far Cheaper Than the Wrong Abstraction

Kelvin Kariuki — Sun, 21 Jun 2026 16:51:05 +0000

Developer Take on: Code Duplication Is Far Cheaper Than the Wrong Abstraction

As developers, we're hardwired to embrace the DRY principle (Don't Repeat Yourself), striving for elegant, reusable code. Yet, this pursuit can sometimes lead us down a treacherous path: premature abstraction. While repetition might feel like a sin, I'm here to tell you that code duplication, when managed intentionally, is often far cheaper than a poorly conceived abstraction.

The Allure and Peril of Premature Abstraction

The drive to abstract is powerful. We envision perfectly modular systems, easily extensible, with every piece fitting neatly into a grand architectural puzzle. We've been taught to spot patterns, extract common logic, and build layers of abstraction to manage complexity. And for good reason – well-designed abstractions are the backbone of maintainable, scalable software.

However, the operative word here is "well-designed." An abstraction that is built too early, before the underlying problems and their evolution are fully understood, becomes a liability. This "wrong abstraction" often manifests as:

Over-engineering: Solutions that are far more complex than the problem they solve, introducing unnecessary layers and indirections.
Rigidity: Abstractions that are hard to change because they've tried to encompass too many potential future scenarios, making them brittle when those scenarios inevitably diverge.
Obscured Intent: The core business logic gets buried under layers of generic interfaces and abstract classes, making the code harder to read, understand, and debug.
Tight Coupling: Paradoxically, an attempt to reduce coupling through abstraction can sometimes lead to different parts of the system becoming implicitly coupled to the abstraction itself, making changes ripple unexpectedly.

The cost of a wrong abstraction is immense. It slows down development, frustrates new team members trying to understand the codebase, makes refactoring a nightmare, and can actively prevent new features from being implemented efficiently. You end up spending more time fighting your own architecture than solving actual user problems.

The Case for Controlled Duplication: "Copy-Paste, but with Intent"

Before you accuse me of heresy, let's clarify: I'm not advocating for mindless copy-pasting or allowing your codebase to devolve into an unmaintainable mess. Instead, I'm suggesting a pragmatic approach: embrace controlled, temporary duplication as a design tool, especially in areas of high uncertainty or rapid evolution.

Think of it this

How to use build-your-own-x: Master programming by recreating your favorite technologies from scratch.

Kelvin Kariuki — Sun, 21 Jun 2026 16:32:40 +0000

Imagine truly understanding how your favorite tools work, not just how to use their APIs. This is the power of "build-your-own-x" – a transformative approach to mastering programming by recreating technologies from scratch.

Master Programming by Recreating Your Favorite Technologies from Scratch

As developers, we often become adept at using frameworks, libraries, and tools, but how deep does our understanding truly go? The "build-your-own-x" philosophy challenges us to move beyond consumption and into creation. It's about taking a technology you use daily – be it a web server, a text editor, a database, or even a simple shell – and attempting to build a simplified version of it yourself. This isn't about reinventing the wheel perfectly, but about understanding the wheel's fundamental mechanics.

Why Rebuild? The Unseen Benefits

The idea of building something that already exists might seem redundant, but the benefits for a developer's growth are profound:

Deepened Understanding: You move from knowing what a tool does to understanding how it does it. You'll grasp the underlying data structures, algorithms, network protocols, and design patterns.
Enhanced Problem-Solving: Breaking down a complex system into its core components forces you to think critically, identify challenges, and devise solutions independently.
Language and Ecosystem Agnosticism: You learn concepts that transcend specific languages or frameworks. A web server's core principles are similar whether implemented in Python, Node.js, or Go.
Improved Debugging Skills: When you've built the system yourself, you inherently know its potential failure points, making debugging much more intuitive.
Unbeatable Portfolio Projects: A self-built, albeit simplified, version of a well-known technology demonstrates initiative, deep understanding, and advanced technical skills to potential employers.
Better Tool Selection: With a grasp of underlying mechanisms, you'll make more informed decisions when choosing existing tools, understanding their trade-offs and efficiencies.

Choosing Your "X": Start Small, Think Big

The key to success with this method is choosing the right "X." Don't start by trying to build a full-fledged operating system.

Start Simple: Good initial projects include:
- A simple HTTP server
- A command-line tool (e.g., grep or cat)
- A basic task manager
- A markdown parser
- A calculator with operator precedence
Pick What You Use: You'll be more motivated if it's something you interact with regularly.
Break It Down: Immediately start thinking about the core components. What's the absolute minimum functionality required? For an HTTP server, it's listening on a port, parsing requests, and sending responses.

The Process: A Step-by-Step Guide

Once you've chosen your "X," follow a structured approach to maximize your learning.

Step 1: Research & Deconstruct

Before you write a single line of code, understand the existing technology.

Read Documentation: Explore official specifications (e.g., HTTP RFCs, database query languages).
Study Open Source: Look at simplified or reference implementations of similar tools. How have others approached the problem?
Identify Core Principles: What are the fundamental algorithms, protocols, or data structures that make it work?

Step 2: Define Core Functionality

Resist the urge to build everything. What's the "minimum viable product" for your "X"?

For a text editor: Open file, edit text, save file. No syntax highlighting, no undo/redo.
For an HTTP server: Handle GET requests, serve static files, basic error handling.

Step 3: Choose Your Tools (and Language)

You're building from scratch, but you're not building a CPU from scratch. Pick a language you're comfortable with, or one you want to learn. Many find Python, Go, or Node.js excellent choices for their clear syntax and standard library features that can abstract away some low-level complexities while still exposing underlying concepts.

Step 4: Build Iteratively, One Component at a Time

This is where the magic happens. Start with the most fundamental piece and build outwards.

Don't try to build the whole thing at once. This leads to frustration.
**Write tests as you go

How to use build-your-own-x: Master programming by recreating your favorite technologies from scratch.

Kelvin Kariuki — Sun, 21 Jun 2026 16:19:10 +0000

Tired of just using frameworks? It's time to truly understand them, from the ground up. Mastering programming isn't about memorizing APIs; it's about deeply grasping the underlying principles, and there's no better way to do that than by building your own versions of existing technologies from scratch.

Master Programming by Recreating Your Favorite Technologies From Scratch

In a world saturated with frameworks, libraries, and abstraction layers, it's easy to get lost in the "how-to-use-it" without ever truly understanding the "how-it-works." The "Build Your Own X" (BYOX) approach challenges this by pushing you to recreate common technologies—a web server, an ORM, a shell, a database, a text editor—with your own hands, lines of code, and raw understanding. This isn't about replacing established tech; it's about forging a profound connection with the fundamentals that power our digital world.

Why "Build Your Own X" is Your Next Big Learning Project

The benefits of the BYOX approach extend far beyond mere curiosity. It's a transformative learning experience that can elevate your programming skills to an entirely new level:

Deep Understanding, Not Just Usage: When you build a web server, you don't just know how to call app.get('/'); you understand HTTP request/response cycles, sockets, concurrency, and how routes are actually matched.
Unmatched Problem-Solving Skills: You'll face countless roadblocks. Each one is an opportunity to research, debug, and innovate, honing your ability to tackle complex challenges.
Debugging Prowess: There's no better way to learn debugging than trying to figure out why your custom HTTP parser is misinterpreting headers or why your tiny database isn't persisting data correctly.
Boosted Confidence: Shipping a working (even if rudimentary) version of a complex piece of software you built yourself is incredibly empowering

Master Programming by Recreating Your Favorite Technologies from Scratch

Kelvin Kariuki — Sun, 21 Jun 2026 16:08:46 +0000


markdown
# Master Programming by Recreating Your Favorite Technologies from Scratch

Have you ever wondered how a database truly works under the hood, or what makes a web server tick? Building your own version of these technologies from scratch isn't just an academic exercise; it's a fast track to deep understanding, unparalleled problem-solving skills, and a fundamental mastery of programming that no tutorial can replicate.

## The "Build Your Own X" Philosophy: Why Recreate the Wheel?

In a world filled with powerful frameworks and robust libraries, the idea of "recreating the wheel" might seem counterintuitive. Why spend weeks building a basic web server when Nginx or Apache exist? Why craft a simple ORM when SQLAlchemy or Hibernate are available?

The answer is simple: to *understand* the wheel, its spokes, its axle, and how it truly delivers motion. The "Build Your Own X" (BYOX) methodology is about demystifying complex systems by breaking them down into their core components and rebuilding them, piece by piece. It's an immersive learning experience that transforms you from a user of tools into an engineer who understands their very foundations.

### What is "Build Your Own X"?

"Build Your Own X" is an active learning approach where you pick an existing piece of technology – whether it's a command-line utility, a web framework, a database, an operating system component, or even a programming language interpreter – and attempt to build a simplified, functional version of it yourself.

**Common "X" examples include:**
*   A basic HTTP server
*   A templating engine
*   A simple key-value store database
*   A regular expression engine
*   A minimal version control system (like Git)
*   A task scheduler
*   A tiny interpreter for a subset of a language

This isn't about outperforming the originals; it's about internalizing the underlying principles, algorithms, and data structures that make them work.

### Why This Approach Works Wonders

1.  **Demystifies Complex Systems:** Instead of treating technologies as black boxes, you open them up and see the gears turning. This removes the intimidation factor from advanced topics.
2.  **Builds Foundational Knowledge:** You'll deeply engage with core computer science concepts: data structures, algorithms, networking protocols, concurrency, parsing, and more.
3.  **Develops Problem-Solving Skills:** You'll encounter countless small and large challenges. Debugging, refactoring, and iterating become second nature, honing your ability to tackle any programming problem.
4.  **Boosts Confidence and Resume:** Completing a BYOX project is a significant achievement. It demonstrates initiative, deep technical understanding, and the ability to see a complex project through – qualities highly valued by employers. It's an excellent talking point in interviews.
5.  **Forces Understanding of Trade-offs:** As you build, you'll constantly make design decisions. This process reveals why existing solutions chose certain architectures over others, providing invaluable insight into system design.

## Choosing Your "X": Where to Start

The key to a successful BYOX journey is selecting the right "X" for your current skill level and interests.

*   **Start Simple, Scale Up:** Don't aim to build the next Linux kernel on your first try. Begin with a manageable project. A simple CLI tool, a basic HTTP server, or a small in-memory database are excellent starting points.
*   **Pick Something You Use and Are Curious About:** Your intrinsic motivation will be your biggest ally. If you love web development, try building a tiny web framework. If you're fascinated by data, tackle a database.
*   **Consider Your Current Skill Level:** If you're new to programming, a simple "to-do" app CLI might be your "X." If you're intermediate, a basic templating engine or a mini HTTP server is great. Advanced developers might tackle a simple compiler or a distributed system.

## The "Build Your Own X" Process: A Step-by-Step Guide

### Phase 1: Research & Deconstruction
Before you write a single line of code, understand what you're trying to build.
*   **Study Existing Solutions:** Read documentation, source code (if open source),

How to use build-your-own-x: Master programming by recreating your favorite technologies from scratch.

Kelvin Kariuki — Sun, 21 Jun 2026 15:59:03 +0000

Deepening your programming knowledge often feels like climbing an endless mountain, but what if the fastest way to the summit was to dismantle and rebuild the very tools you use daily? Master programming by recreating your favorite technologies from scratch and unlock an unparalleled understanding of how systems truly work.

Build Your Own X (BYOX): The Ultimate Learning Strategy

We've all used frameworks, libraries, and tools that abstract away immense complexity. While incredibly efficient for building applications, relying solely on them can leave gaps in our fundamental understanding. This is where "Build Your Own X" (BYOX) comes in: a powerful learning methodology where you recreate simplified versions of existing technologies from first principles.

Imagine building a basic web server, a tiny ORM, a minimal database, or even a simple shell. Instead of just using Express.js, you'd implement the core request-response cycle. Instead of querying PostgreSQL, you'd design a simple storage and retrieval mechanism. This isn't about reinventing the wheel perfectly; it's about understanding the spokes, the hub, and the tire itself.

Why Embrace BYOX? The Unmatched Benefits

Deepen Foundational Understanding: You move beyond surface-level usage to grasp the underlying algorithms, data structures, and architectural patterns. You'll truly understand why certain design choices were made.
Sharpen Problem-Solving Skills: Encountering and overcoming the challenges of building complex systems from scratch hones your analytical and problem-solving abilities like no other exercise. You'll learn to break down monumental tasks into manageable pieces.
Boost Debugging Prowess: When you understand every layer of your own creation, debugging becomes less about trial-and-error and more about logical deduction. You'll develop an intuition for where issues might lie.
Gain Unshakeable Confidence: Successfully building a simplified version of a system you once considered magic is incredibly empowering. This confidence translates to tackling any new technology with less apprehension.
Appreciate Abstractions and Trade-offs: You'll gain a profound appreciation for the design decisions and compromises made by the creators of the tools you use daily. This insight helps you choose the right tools for future projects and use them more effectively.

How to Approach BYOX: A Step-by-Step Guide

Embarking on a BYOX project might seem daunting, but by following a structured approach, you can turn ambitious ideas into tangible learning experiences.

Choose Your Target Wisely: Start with something you use frequently and can conceptually understand, even if you don't know the implementation details. Good first projects include:
- A simple HTTP server
- A basic grep utility
- A miniature key-value store
- A small command-line task manager
- A URL shortener
- A tiny templating engine
Deconstruct the "Original": Before you write a single line of code, spend time researching how the existing technology works at a high level. What are its core responsibilities? What inputs does it take, and what outputs does it produce? What protocols or standards does it adhere to? This phase is crucial for defining the scope of your own project.
Start with the Minimal Viable Product (MVP): Don't try to build the entire system at once. Identify the absolute core functionality and focus solely on implementing that. For an HTTP server, this might mean just accepting a connection and sending a "Hello, World!" response. For a key-value store, it's simply put(key, value) and get(key).
Iterate and Expand Incrementally:

How to use build-your-own-x: Master programming by recreating your favorite technologies from scratch.

Kelvin Kariuki — Sun, 21 Jun 2026 15:48:30 +0000

Master Programming by Recreating Your Favorite Technologies From Scratch

Ever felt like you're just assembling components without truly understanding how they work? The "build-your-own-X" approach is your ultimate antidote, transforming you from a consumer of tools into a master craftsman who understands the very foundations of technology.

Why "Build-Your-Own-X" is Your Next Programming Superpower

In a world overflowing with frameworks, libraries, and managed services, it's easy to get lost in abstraction. While these tools boost productivity, they can sometimes obscure the fundamental principles upon which they're built. The "build-your-own-X" methodology involves recreating existing, often complex, technologies from scratch. Imagine building a tiny version of Git, a simple web server, or even a basic database. This isn't about reinventing the wheel for production use; it's about deconstructing, understanding, and rebuilding to solidify your programming knowledge like never before.

Here's why this approach is incredibly powerful for your development career:

Deep Understanding of Fundamentals: You'll grasp the core data structures, algorithms, and design patterns that underpin popular technologies. No more black boxes – you'll see inside.
Enhanced Problem-Solving Skills: Breaking down a complex system into manageable parts forces you to think critically and architect solutions from the ground up.
Superior Debugging Prowess: When you build it yourself, you understand every line of code, making you exceptionally skilled at finding and fixing issues.
Confidence and Empowerment: Successfully building a simplified version of a system like a database or a blockchain gives you immense confidence in your abilities and demystifies seemingly complex concepts.
Impressive Portfolio Projects: "I built a tiny Git clone" or "I wrote my own HTTP server" makes for incredibly compelling portfolio pieces and interview talking points.
Breaking Free from Tutorial Hell: This hands-on, project-based learning keeps you engaged and forces you to apply knowledge actively, rather than passively following instructions.

Choosing Your "X": Where to Start?

The key to a successful "build-your-own-X" journey is selecting the right "X."

Start Small and Simple: Don't aim to build the next Facebook. Focus on the core functionality.
Pick Something You Use Regularly: Familiarity with the end-user experience helps guide your design.
Clear Scope: Define the minimum viable product (MVP) features early to prevent scope creep.
Good Learning Resources Exist: While you're building from scratch, understanding how the original works (conceptually) is crucial. Look

Developer take on: (How to Write a (Lisp) Interpreter (In Python))

Kelvin Kariuki — Sun, 21 Jun 2026 15:42:21 +0000

Developer Take on: How to Write a (Lisp) Interpreter (In Python)

Ever wondered how your favorite programming language truly works under the hood? Or how a new programming language comes to life? Building an interpreter from scratch is a profound journey into the core mechanics of computation, and there's no better starting point than Lisp, implemented in Python.

This isn't just

DEV Community: Kelvin Kariuki

How to use public-apis: A collective list of free APIs

Discovering Your API Playground: The public-apis Repository

Navigating the Treasure Trove

Choosing Your First Public API: Key Considerations

Master Programming by Recreating Your Favorite Technologies From Scratch

Master Programming by Recreating Your Favorite Technologies From Scratch

The "Build-Your-Own-X" (BYOX) Philosophy: Unlocking Deeper Understanding

Choosing Your "X": Start Small, Think Big

Developer take on: Code duplication is far cheaper than the wrong abstraction (2016)

The Allure of Abstraction

The Heavy Toll of the Wrong Abstraction

Developer take on: (How to Write a (Lisp) Interpreter (In Python)) (2010)

Developer Take On: How to Write a (Lisp) Interpreter (In Python) (2010 Edition, Revisited)

The Interpreter's Anatomy: A Three-Act Play

Act 1: The Lexer – Breaking Down the Walls of Text

Developer take on: Code duplication is far cheaper than the wrong abstraction

Developer take on: Code duplication is far cheaper than the wrong abstraction

Developer Take on: Code Duplication Is Far Cheaper Than the Wrong Abstraction

Developer Take on: Code Duplication Is Far Cheaper Than the Wrong Abstraction

The Allure and Peril of Premature Abstraction

The Case for Controlled Duplication: "Copy-Paste, but with Intent"

How to use build-your-own-x: Master programming by recreating your favorite technologies from scratch.

Master Programming by Recreating Your Favorite Technologies from Scratch

Why Rebuild? The Unseen Benefits

Choosing Your "X": Start Small, Think Big

The Process: A Step-by-Step Guide

Step 1: Research & Deconstruct

Step 2: Define Core Functionality

Step 3: Choose Your Tools (and Language)

Step 4: Build Iteratively, One Component at a Time

How to use build-your-own-x: Master programming by recreating your favorite technologies from scratch.

Master Programming by Recreating Your Favorite Technologies From Scratch

Why "Build Your Own X" is Your Next Big Learning Project

Master Programming by Recreating Your Favorite Technologies from Scratch

How to use build-your-own-x: Master programming by recreating your favorite technologies from scratch.

Build Your Own X (BYOX): The Ultimate Learning Strategy

Why Embrace BYOX? The Unmatched Benefits

How to Approach BYOX: A Step-by-Step Guide

How to use build-your-own-x: Master programming by recreating your favorite technologies from scratch.

Master Programming by Recreating Your Favorite Technologies From Scratch

Why "Build-Your-Own-X" is Your Next Programming Superpower

Choosing Your "X": Where to Start?

Developer take on: (How to Write a (Lisp) Interpreter (In Python))

Developer Take on: How to Write a (Lisp) Interpreter (In Python)

Discovering Your API Playground: The `public-apis` Repository