The Invisible Wall Between Coding and Engineering

In the world of software development, there is a critical moment that even the most experienced teams face—a moment where everyone initially agrees at the start, only to end up blaming one another halfway through. An idea is put on the table, excitement is high, and that impatient question fills the room:

"When do we start writing the code?"

This question sounds like the most natural, business-oriented, and results-driven inquiry possible. After all, we are building a software project, right? Therefore, someone must sit at the keyboard and start writing those magic lines. However, in our industry, starting is often confused with being ready. You do not need to pour concrete to start a construction project; first, you must conduct a site survey, calculate statics, and finalize the architectural blueprints. In software, this invisible wall is often ignored.

The fundamental problem here is the misconception that software development and coding are synonymous. Coding is simply translating defined logic into machine language. Software development, on the other hand, is the engineering process that determines what that logic should be, how it will solve a problem, and the constraints within which the system will exist. You can release an app by only coding, but you cannot build a sustainable product without software engineering.

Our experience shows a clear reality: projects fail not because of technical incompetence, but because of the "we know what we are doing" assumption, which leads to pushing ahead before technical details are clarified. Those few weeks seemingly gained at the beginning transform into months of bug fixing and refactoring at the end.

The Illusion of Progress: Why We Crave Visible Screens

Human psychology is programmed to be satisfied by tangible data. Spending hours in a meeting room drawing flowcharts, discussing database relationships, or writing user stories feels like "spinning the wheels" to many entrepreneurs and managers. This is because, at the end of the day, there is no "working" product—only documents, diagrams, and notes.

However, when a developer says, "I finished the login screen; when you click the button, the home page opens," and shows it to you, it creates a dopamine hit in the brain. The feeling of "It works! We are moving forward!" is the project's greatest narcotic. This feeling is so powerful that it masks the underlying chaos.

  • The login screen exists, but is the Role-Based Access Control matrix defined?
  • The page opens when the button is clicked, but how is Data Integrity maintained in the database?
  • We are moving forward, but in which direction?

This Illusion of Progress has deepened with the misunderstanding of agile methodologies. The "build it as you go" mentality translates to "technical debt accumulates as you go and eventually bankrupts you" in software engineering. Wanting to see code too early is like ordering windows before laying the foundation of a building. You are happy when the windows arrive, but that happiness turns into panic when you realize there are no walls to install them on.

The 90% Syndrome: Why Projects Die at the Finish Line

The biggest symptom of premature coding is the 90% Syndrome, a phenomenon that is often joked about in the industry but is actually tragic. The first half of the project timeline goes great. Screens appear quickly, demos are conducted, and everything seems fine. The project appears to be 90% complete. Yet, that final 10% takes up twice the total time allocated for the entire project.

Why does this happen?

Because that initial 90% represents the Happy Path—scenarios where everything goes right. The user clicks the right button, the internet does not cut out, the server does not return an error, and the credit card limit is sufficient. Coding this is relatively easy.

However, the final 10% is the real world, and it is where true software engineering begins:

  • Edge Cases: What happens if the internet cuts out while the user is making a payment, and the money is withdrawn but the order is not created? (Transaction Management)
  • Behavior Under Load: What if the system, which worked perfectly for 5 testers, locks the database when 5,000 people access it simultaneously? (Deadlocks)
  • Data Sanitization: How will the system clean input if a user enters emojis, SQL injection code, or unexpected characters into a form?

Teams that start coding too early often fail to ask these questions at the beginning, forcing them to change the entire architecture at the end. The code you write to manage errors (Exception Handling) is often longer than the code that performs the primary task. If you did not design for this from the start, you begin patching your code at the final stage. A project that turns into a "patchwork quilt" can never truly launch—or if it does, it becomes a Zombie Project; it neither lives nor dies.

The Unforgiving Nature of Database Schemas

In software, changing code is easy, and changing the user interface is very easy; however, changing the Database Schema is difficult and costly. A rushed database design made at the beginning seals the fate of the project.

For example, imagine you combined the "Product" and "Price" tables in an e-commerce project for the sake of speed. Six months later, when the business unit says, "We now want to show dynamic prices based on the customer group or the time of day," that simple table structure becomes a shackle.

"Data lives longer than code. You can delete your code, but you can rarely delete your data."

To make that change, you must modify thousands of lines of legacy code, rewrite all reports, and perform data migrations that risk live information. Therefore, before you start writing code, you must simulate how data will flow, where it will be stored, and how it will be related on paper. One day spent in this phase saves a month in the future.

The Behavioral Trap: The "Fix it Later" Lie

Under tight schedules, developers often retreat to the most common white lie in software: "Let's release it like this for now; we will refactor it later". In the commercial world, spending money to go back and fix working code is almost never a priority for a business unit.

These temporary solutions accumulate within the code. We call this Technical Debt. Just like financial debt, technical debt has interest. Every new feature added on top of "dirty" code is developed more slowly and produces more bugs. Eventually, you spend all your time paying interest (fixing bugs) and have no time left to pay down the principal (developing new features). The team slows down, motivation drops, and the project sinks into a quagmire.

Technical debt is not born of malice, but of quality compromises made under the pressure of "speed". And these compromises are most frequently made at the very beginning, when we start coding before we fully understand what we are building.

Wrongful Accusations: Technology or Architecture?

When a project stalls, a scapegoat is usually sought, and the bill is often charged to the technology stack:

  • "We wrote it in PHP, that's why it happened; if we used Go, it would fly."
  • "We built a monolith; we should have used Microservices."
  • "If we used NoSQL instead of SQL, none of this would have happened."

These approaches are defense mechanisms that miss the root cause. Poor architecture produces poor results even in the fastest language in the world. A well-designed monolith is far more performant, manageable, and cost-effective than a poorly designed microservices architecture.

The problem is not the hammer you are using; it is that you are hitting the glass instead of the pillar. Chasing technological "hypes" and incorporating complex structures that do not fit the project's requirements only increases maintenance costs. Simplicity is the most difficult level to reach in software engineering, and it is reached through thinking, not rushing.

The Solution: The Boring Software Manifesto

Writing code unplanned with exciting technologies is fun but leads to disaster. Sustainable success lies in the principles of Boring Software. These principles mandate:

1. Freeze the Schema Before Writing Code

How data flows is more important than the code itself. Discuss the database design with your team, draw it on a whiteboard, and simulate edge cases. Never start a project without an Entity-Relationship (ER) diagram.

2. Define the Boundaries

What a module will not do must be as clear as what it will do. Scope Creep is the inevitable result of projects without defined boundaries. Every "let's add this too" feature increases testing and maintenance costs geometrically.

3. Design for Exceptions

Anyone can code the Happy Path. You should think about the moments when the system will break. When the internet drops, when a service does not respond, or when a credit card limit is insufficient, will your system simply say "Unknown Error," or will it recover the process?

Those who rush to start a software project are actually rushing toward failure. The right question is not "When do we start coding?" but "Are we sure about what we are coding and the associated risks?". You cannot solve a problem in a code editor that you have not solved on paper. The real loss of time is not stopping to think; it is running in the wrong direction.