My Mental Model for Writing Simpler Backend Systems

After enough APIs built, legacy systems refactored, and late night production incidents, something started to become obvious: backend engineering is not about frameworks. It is about reducing chaos.

Which caos you ask?

I know, this sounds like a goofy tech coach quote, but is the reality. The client doesn't care about our event based systems, CQRS and AWS, they want a report when they click the blue button, a cheaper infra and the most specific possible business rules on production.

That creeping disorder even has a name: code entropy the natural tendency of systems to drift toward complexity and disorder as they grow, requirements shift, and teams change.

Reducing the said chaos is not easy, and to aid myself i have this is the mental model I try to follow when I write code. It's not perfect. It's not finished. It's what I aim for.

1. My job is to reduce chaos

Systems grow, rules change, people leave. If the system becomes harder to reason about over time, I failed. Backend exists to create boundaries, clear ones. And that's it. Computers are designed to be predictable machines, and our code should be designed with this on mind.

2. Business rules are sacred

Frameworks change, cloud providers change, databases change. Business rules stay. I try to keep domain logic isolated, avoid coupling rules to transport (HTTP, queues), and test rules independently from infrastructure. Infrastructure serves the domain, never the opposite.

This sounds obvious until you're three sprints deep into a codebase where the business logic lives inside a controller.

3. Clarity beats cleverness

If I need to explain it twice, it's too complex. I prefer explicit names, small functions, predictable flow, and less magic. Code should feel boring and stable. The kind of code you open six months later and immediately understand. That's the goal, like a old school COBOL system.

4. Design for today, evolve when it hurts

I don't optimize for imaginary scale. I solve the current problem well, then I observe. Premature complexity is just ego disguised as foresight. We've all done it, it's never worth it.

5. Failure is expected

Networks fail, dependencies fail, people make mistakes. Good backend systems fail predictably, log with context, avoid corrupting state, and prefer idempotent operations when possible. Resilience is intentional. You don't stumble into it.

6. Decisions must be reversible when possible

Not every decision needs a committee. If it's reversible, I decide. If it's expensive, I document and chat with my Lead. Progress beats paralysis, we do async work. And most decisions are more reversible than they feel in the moment.

7. Production is the final judge

Opinions don't matter more than logs, metrics, and real user behavior. If it's not observable, it's not reliable. No matter how elegant the architecture looks on a whiteboard.

8. Simplicity is responsibility

The goal is not to impress. The goal is to make the system understandable for the next engineer, including future me. And the 10PM future me is always more tired and less patient than present 9AM me.

Closing Thought

This is not rocket science. Backend is not about being brilliant. It's about building systems that survive change, entropy, and people. Do good work. That's the standard.