Developer Philosophy: Craft Over Speed

Why I reject the 'just make it work' mentality and how building elegant systems pays off in the long run. Code is not disposable.

I'm Not a Standard Developer

For me, coding is not a profession, it's a craft.

I reject the "just make it work" mentality that most developers have. For me, it's not enough for code to just work; it also needs to be elegant, efficient, and future-oriented. I am an architect who builds performant and scalable systems in the digital world, thought through to the finest detail.

The Perfectionist Obsession

I obsess over code — and I'm proud of it.

I don't just solve the problem. I don't sleep until I find the most optimized, most performant, and most secure version of that solution. Even a millisecond delay is a defeat for me. This perfectionist obsession is actually a reflection of my respect for the user.

// Bad: Just making it work
func GetUser(id int) User {
    // Direct database query in handler
    // No caching, no error handling
    return db.Query("SELECT * FROM users WHERE id = ?", id)
}

// Good: Obsessing over the details
func GetUser(ctx context.Context, id int) (*User, error) {
    // Check cache first
    if cached := cache.Get(ctx, userCacheKey(id)); cached != nil {
        return cached, nil
    }

    // Query with timeout and proper error handling
    user, err := userRepo.FindByID(ctx, id)
    if err != nil {
        return nil, fmt.Errorf("failed to fetch user: %w", err)
    }

    // Cache for future requests
    cache.Set(ctx, userCacheKey(id), user, 5*time.Minute)

    return user, nil
}

Every line matters. Every function signature is a contract. Every error path is considered.

Building Earthquake-Resistant Skyscrapers

I don't just stack bricks on top of each other; I lay the foundation of earthquake-resistant skyscrapers that will stand for years.

Clean Architecture, SOLID principles — these aren't just buzzwords for me, they're my life philosophy. Under every line of code I write lies not just logic, but a vision.

The Foundation Matters

Most developers rush to build features. I start by asking:

How will this scale to 100,000 users?
What happens when this service goes down?
Can a junior developer understand this code in 6 months?
Will this architecture still make sense in 5 years?

┌─────────────────────────────────────┐
│         Presentation Layer          │  ← Clean, simple interfaces
├─────────────────────────────────────┤
│         Application Layer           │  ← Business logic
├─────────────────────────────────────┤
│           Domain Layer              │  ← Core entities
├─────────────────────────────────────┤
│       Infrastructure Layer          │  ← Database, APIs, etc.
└─────────────────────────────────────┘

Each layer has a purpose. Each boundary is protected. Each dependency points inward.

Conscious Technology Choices

I tried popular paths like TypeScript/Next.js, but consciously abandoned them because I couldn't foresee the future.

My choice of Go isn't just a language preference; it's because it represents the philosophy of performance, simplicity, and scalability. Instead of chasing trends, I invest in technologies that will still be relevant ten years from now.

Why Go?

Performance: Compiled, statically-typed, concurrent by design
Simplicity: No classes, no inheritance, no magic
Scalability: Built for distributed systems from day one
Longevity: Backed by Google, stable API, backward compatible

// This is all you need for a concurrent, production-ready HTTP server
func main() {
    mux := http.NewServeMux()
    mux.HandleFunc("/health", healthCheck)

    server := &http.Server{
        Addr:         ":8080",
        Handler:      mux,
        ReadTimeout:  10 * time.Second,
        WriteTimeout: 10 * time.Second,
        IdleTimeout:  120 * time.Second,
    }

    log.Fatal(server.ListenAndServe())
}

No frameworks. No abstractions. Just code that works and will continue to work.

User-Centric Perfectionism

All this "obsessing" has one purpose: To provide users with a fast, reliable, and seamless experience.

My perfectionism is actually my customer satisfaction obsession. Because coding is an art form for me, and like every work of art, the systems I create must add value to users' lives.

What This Means in Practice

Performance: Sub-200ms API response times, not "good enough"
Reliability: 99.9% uptime with graceful degradation, not "it usually works"
Security: Defense in depth, not "we haven't been hacked yet"
Monitoring: Observability from day one, not "let's add logs later"

Every millisecond matters. Every edge case is considered. Every failure mode is handled.

The Five-Year Principle

"I write code thinking not just about today, but about what a system will look like five years from now. Every line of code is a step taken to prevent a future problem or create an opportunity."

This is my guiding principle. When I write code, I ask:

Will this scale? Not to 1000 users, but to 1 million
Can this be maintained? Not by me, but by someone who joins next year
Is this testable? Not just unit tests, but integration and load tests
Is this observable? Can I debug this at 3 AM when production is down?
Is this secure? Not against script kiddies, but against sophisticated attacks

Real Example: Database Design

-- Bad: Quick and dirty
CREATE TABLE users (
    id INT PRIMARY KEY,
    name VARCHAR(255),
    email VARCHAR(255)
);

-- Good: Thinking five years ahead
CREATE TABLE users (
    id BIGSERIAL PRIMARY KEY,
    uuid UUID NOT NULL UNIQUE DEFAULT gen_random_uuid(),
    email VARCHAR(320) NOT NULL UNIQUE,
    email_verified BOOLEAN NOT NULL DEFAULT FALSE,
    name VARCHAR(255) NOT NULL,
    created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
    updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
    deleted_at TIMESTAMPTZ,
    CONSTRAINT email_format CHECK (email ~* '^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}$')
);

CREATE INDEX idx_users_email ON users(email) WHERE deleted_at IS NULL;
CREATE INDEX idx_users_created_at ON users(created_at DESC);

-- Trigger for updated_at
CREATE TRIGGER update_users_updated_at
    BEFORE UPDATE ON users
    FOR EACH ROW
    EXECUTE FUNCTION update_updated_at_column();

The second approach:

Scales to billions of rows (BIGSERIAL)
Supports distributed systems (UUID)
Handles soft deletes (deleted_at)
Validates data at database level
Optimized for common queries
Tracks changes automatically

The Cost of Craft

Yes, building this way takes more time upfront. But the payoff is exponential:

Fewer bugs in production
Faster feature development after the foundation is solid
Lower maintenance costs over time
Easier onboarding for new developers
Better sleep knowing the system won't randomly crash

I've seen too many "quick and dirty" solutions become million-dollar technical debt nightmares.

My Commitment

When you work with me, you get:

Production-ready code from day one
Architecture that scales
Tests that give confidence
Documentation that makes sense
Monitoring that catches issues before users do

Not because I'm trying to be perfect. But because this is the only way I know how to build.

The Bottom Line

Coding is a craft. Systems are art. Users deserve excellence.

I don't build software to just check boxes. I build systems that last, scale, and delight.

That's not standard developer work. That's craftsmanship.

If this philosophy resonates with you, let's work together. If you think it's overkill, that's fine — there are plenty of developers who will build you a "quick solution." Just don't call me when it breaks in production.