As engineers, it’s easy to get lost in the weeds. We dive deep into solving problems, chasing edge cases and perfect logic, but sometimes forget to focus on the core of what actually needs to work. It’s natural—we want to get things right. But often, the “right thing” is just getting a simple, functional version working first.

Let’s look at a couple of examples that highlight this idea.

A Real-World Example

Disclaimer: This is based on a real problem I encountered, but the details have been changed to protect the innocent.

I worked on a project for a client who needed a desktop application to interact with a third-party system. This system managed resources moving through a pipeline—buying, selling, storing, moving, or releasing them. Each action required input, like filling out a form, but the required fields changed based on the action. Some inputs were simple text, others dropdowns populated dynamically from the backend or the third-party system.

The client’s users were used to spreadsheets and wanted a similar experience. A wizard-style UI was a no-go—too slow. Instead, they needed a fast, reactive interface: select an action, and the relevant fields would update immediately. On paper, it didn’t sound too bad. In practice, it was a beast.

The project was already behind schedule and over budget. The previous dev team had been let go, and we were asked to pick up the pieces—without starting over.

Every action in the app was broken in some way. Some hadn’t even been started. The previous team had tried to implement every single business rule from the beginning, action by action. But each fix broke something else. The codebase was a mess.

So we took a different approach.

We stripped the business logic out. Completely. Just commented it out. We replaced everything with basic inputs and dropdowns that passed data through to the backend without validation—except for the action selector, which was still wired up to dynamically control the form.

Suddenly, we had something that worked. The third-party integration—the actual root problem—was functional. That was the turning point.

Once we had a working foundation, we reintroduced business rules one at a time, testing and validating each as we went. We delivered a working system on time.

The lesson? The complicated business logic wasn’t the real blocker—it was trying to solve everything at once without a stable base. Once we focused on the core problem, the rest fell into place.

Another Example

Let’s say you’re building a CSV importer. The goal? Read a CSV file, validate it, and insert the data into a database.

Sounds simple—until validation enters the picture.

Now you’re dealing with required fields, optional fields, special formats, external API checks, inconsistent headers, mixed casing, varying column orders, and more.

That’s a lot. And it’s tempting to start coding all those checks from the beginning. But again, what’s the real problem?

You need to get data from a file into the database. That’s the heart of it.

So start there. Build an importer that reads the file and inserts the raw data. Don’t worry about all the edge cases just yet. Once the core path works, layer in the validation rules step by step. That way, you always have something functional, and you’re never completely blocked.

The Moral

Complexity is seductive. It can trick you into thinking it’s the main problem.

But it often isn’t.

Start with the root issue—the one thing that absolutely has to work. Strip it down to its essentials and get that part solid. Once the foundation is in place, you can build complexity with confidence.

Don’t get bogged down in the details before you have something working.

Because at the heart of it all, what really matters is delivering something real.