When we design software, it’s tempting to build for permanence. We fall in love with our choices—this database, that messaging queue, that perfect-looking third-party service—and we wire them in like they’ll be with us forever. But here’s the uncomfortable truth: the real world doesn’t care about your confidence in a decision you made six sprints ago.
Things change. Requirements shift. Tools reveal their limitations. What seemed like a perfect fit at design time often shows its cracks in production.
That’s why we should build for replacability.
Not because we plan to replace things—but because we might.
When you assume something is temporary, you force yourself to abstract it, isolate it, contain the blast radius. You make it modular. You keep boundaries sharp. You leave doors open for future you to walk through with minimal pain.
And the best part? This doesn’t just help you swap out tools—it changes how you think.
Designing for replacability creates a tight feedback loop. You take action. Action produces real data. That data leads to clarity. And clarity leads to better systems.
We often waste time arguing about hypothetical problems, trying to pre-solve everything with upfront brilliance. But speculation is a poor substitute for experience.
The faster you can try, learn, and swap, the faster you move toward the architecture your system actually needs.
Want to switch from RabbitMQ to Kafka later? Cool. Just don't bake RabbitMQ assumptions deep into your domain logic.
Want to replace an in-house service with a SaaS API? Awesome. Just keep the interface clean.
Want to migrate from MongoDB to Postgres? No problem—if your data access layer isn’t a tangled mess of collection-specific code.