Software & Systems Engineering

How We Think About Engineering

Good engineering isn't about using the latest framework or following trends. It's about solving problems correctly—building systems that work, scale, and don't fall apart when the original developers leave.

We've inherited enough legacy systems to know what bad engineering looks like. Undocumented code. Brittle architectures. "It works, don't touch it" components that everyone's afraid to modify. Tests that don't run. Deployments that require tribal knowledge.

Our engineering philosophy is simple: build things right the first time, so you're not rebuilding them forever.

The best code is code you don't have to think about. It just works, it's obvious what it does, and it's easy to change.

That doesn't mean over-engineering. It means making the right trade-offs for your situation. Sometimes that's a simple script. Sometimes that's a distributed system. The skill is knowing which one you actually need.

Full-Stack: What We Actually Do

"Full-stack" is often meaningless buzzword. Here's what it means for us:

We're not a shop that outsources parts we can't do. When you work with us, one team handles everything. That means fewer handoffs, fewer integration problems, and someone who actually understands the whole system.

Backend Architecture

The backend is where business logic lives. Get it wrong, and everything else suffers.

Service Design

We design backends around your domain, not around technical patterns. Services map to business capabilities, not arbitrary technical boundaries.

// Good: Service matches business concept
class OrderService {
  async createOrder(cart: Cart, customer: Customer): Promise<Order> {
    // All order-related logic in one place
    const order = await this.validateAndCreate(cart, customer);
    await this.calculatePricing(order);
    await this.reserveInventory(order);
    await this.notifyFulfillment(order);
    return order;
  }
}

// Bad: Technical layers that fragment business logic
class OrderController { /* HTTP only */ }
class OrderRepository { /* DB only */ }
class OrderValidator { /* validation only */ }
// Business logic scattered across files

API Design

APIs are contracts. Once published, they're hard to change. We design them carefully.

RESTful When It Fits

For most CRUD operations and straightforward resources, REST is clean and predictable.

// Clear, predictable REST endpoints
GET    /api/v1/orders              // List orders
GET    /api/v1/orders/:id          // Get specific order
POST   /api/v1/orders              // Create order
PATCH  /api/v1/orders/:id          // Update order
DELETE /api/v1/orders/:id          // Cancel order

// Nested resources when they make sense
GET    /api/v1/orders/:id/items    // Order line items
POST   /api/v1/orders/:id/refunds  // Create refund

GraphQL When Needed

For complex, interconnected data with varying client needs, GraphQL shines.

# Client requests exactly what they need
query OrderDetails($id: ID!) {
  order(id: $id) {
    id
    status
    total
    items {
      product { name, image }
      quantity
      price
    }
    customer {
      name
      email
    }
    shipments {
      carrier
      tracking
      estimatedDelivery
    }
  }
}

Data Layer

Database design is critical. Poor data modeling causes endless problems.

-- Example: Order schema with thought-out indexes
CREATE TABLE orders (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  customer_id UUID NOT NULL REFERENCES customers(id),
  status VARCHAR(50) NOT NULL DEFAULT 'pending',
  total_cents INTEGER NOT NULL,
  currency VARCHAR(3) NOT NULL DEFAULT 'EUR',
  created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
  updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);

-- Indexes for actual query patterns
CREATE INDEX idx_orders_customer ON orders(customer_id);
CREATE INDEX idx_orders_status_created ON orders(status, created_at DESC);
CREATE INDEX idx_orders_created ON orders(created_at DESC);

Frontend Architecture

Frontends get complicated fast. Users expect snappy interfaces, offline support, real-time updates, and flawless mobile experiences. Here's how we deliver.

Component Architecture

We build frontends from composable, reusable components. Not because it's trendy, but because it actually works.

// Component hierarchy for an order page
<OrderPage>
  <OrderHeader order={order} />
  <OrderItems items={order.items} />
  <OrderSummary
    subtotal={order.subtotal}
    shipping={order.shipping}
    tax={order.tax}
    total={order.total}
  />
  <OrderActions
    order={order}
    onCancel={handleCancel}
    onRefund={handleRefund}
  />
</OrderPage>

Smart vs. Dumb Components

Smart components manage state and logic. Dumb components just render what they're given.

This separation makes testing easy. Dumb components are trivial to test—just pass props and check output.

State Management

State management is where many projects go wrong. Either too much (Redux for a todo app) or too little (prop drilling through 10 levels).

Our approach:

// Local state for component-specific concerns
const [isOpen, setIsOpen] = useState(false);

// Server state with React Query / SWR
const { data: orders, isLoading } = useQuery({
  queryKey: ['orders'],
  queryFn: fetchOrders
});

// Global state for truly app-wide concerns
// (user session, theme, feature flags)
const { user } = useAuth();
const { theme } = useTheme();

Performance

Slow frontends lose users. We optimize from the start.

// Code splitting with Next.js
const HeavyComponent = dynamic(() => import('./HeavyComponent'), {
  loading: () => <Skeleton />,
  ssr: false
});

// Image optimization
<Image
  src="/product.jpg"
  alt="Product"
  width={400}
  height={300}
  placeholder="blur"
  priority={isAboveFold}
/>

Infrastructure & DevOps

Code that can't be deployed reliably isn't done. Infrastructure is part of engineering.

Infrastructure as Code

Everything is code. Infrastructure, configuration, policies. All version-controlled, all reviewable.

# Terraform example: Production-ready EKS cluster
module "eks" {
  source  = "terraform-aws-modules/eks/aws"
  version = "~> 19.0"

  cluster_name    = "production"
  cluster_version = "1.28"

  vpc_id     = module.vpc.vpc_id
  subnet_ids = module.vpc.private_subnets

  eks_managed_node_groups = {
    general = {
      min_size     = 2
      max_size     = 10
      desired_size = 3

      instance_types = ["t3.large"]
      capacity_type  = "ON_DEMAND"
    }
  }
}

CI/CD

Every commit triggers a pipeline. Tests run. Code gets reviewed. Deployments happen automatically.

# GitHub Actions pipeline
name: Deploy
on:
  push:
    branches: [main]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: npm ci
      - run: npm test
      - run: npm run lint
      - run: npm run type-check

  deploy:
    needs: test
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Deploy to production
        run: |
          # Blue-green deployment
          ./scripts/deploy.sh production

Monitoring & Observability

You can't fix what you can't see. We instrument everything.

// Structured logging example
logger.info('Order created', {
  orderId: order.id,
  customerId: customer.id,
  total: order.total,
  items: order.items.length,
  duration: performance.now() - startTime
});

Engineering Standards

Standards make teams effective. Here's what we enforce.

Code Quality

// TypeScript strict config
{
  "compilerOptions": {
    "strict": true,
    "noUncheckedIndexedAccess": true,
    "noImplicitReturns": true,
    "noFallthroughCasesInSwitch": true,
    "exactOptionalPropertyTypes": true
  }
}

Code Review

Every change gets reviewed. Not as a formality, but as a genuine quality gate.

What we look for:

• Does it solve the right problem?
• Is the approach reasonable?
• Are there edge cases unhandled?
• Is it testable and tested?
• Will future developers understand it?

Documentation

Code should be self-documenting where possible. But systems need docs.

What we document:
├── Architecture decisions (ADRs)
├── API documentation (OpenAPI)
├── Runbooks for operations
├── Onboarding guides
└── Decision rationale (why, not just what)

Security by Default

Security isn't a feature—it's a fundamental requirement.

// Example: Secure API endpoint
app.post('/api/orders',
  authenticate(),           // Verify identity
  authorize('orders:write'), // Check permission
  validateInput(orderSchema), // Sanitize input
  rateLimit({ max: 100 }),  // Prevent abuse
  async (req, res) => {
    // Business logic here
  }
);

How We Work with Clients

Engineering isn't just about code. It's about solving your problems.

We start by understanding your business. Not just the technical requirements, but why they matter. What's the goal? What's the constraint? What happens if we get it wrong?

We communicate constantly. Weekly syncs, async updates, transparent access to everything we're building. No surprises.

We deliver incrementally. Not a big bang after months of silence, but working software every sprint. You see progress, you can give feedback, you can course-correct.

We transfer knowledge. Our goal is for your team to own and maintain everything we build. That means documentation, training, and pair programming when it helps.

Conclusion

Good software engineering is a craft. It's not about following frameworks blindly or using whatever's newest. It's about making thoughtful decisions, writing code that lasts, and building systems that actually solve problems.

The best engineering feels boring. Systems that just work. Code that's obvious. Deployments that are non-events.

That's what we deliver. Not exciting demos that fall apart in production, but reliable systems that compound value over time.

If you're building something that matters, we'd be happy to talk.