University grades you on how much you know, so complex code scores well. Customers grade you on one thing: does the product solve their problem, fast?
That gap is where over-engineering comes from. The fix is to build the simplest thing that works, and add complexity only when real users need it.
I see both grading systems up close. I finished my Master's degree in Artificial Intelligence in June 2026 while building products for businesses, and the two reward almost opposite habits.
What is over-engineering?
Over-engineering is building software more complex than the problem needs. It means adding layers, tools and features for users and problems you don't have yet.
Think of a math exam. The teacher gives marks for showing every step, so long answers score well.
A customer is not a teacher. They only want the answer, and every extra step is time they wait.
Over-engineering makes a product slower to build, harder to change and more expensive to run. And the customer never sees any of it.
Why does university reward complexity?
Because a university project has a different job. It must prove you understand the theory.
A detailed database design, a clever algorithm and several architecture layers all show knowledge. The jury sees the effort, so the effort earns marks.
That is not wrong. The foundations you learn at university are real, and you will need them. The problem is the habit: carrying "complex means good" into a business where nobody is grading complexity.
What does over-engineering look like in a startup?
The same patterns come back again and again:
- Microservices for five users. Splitting the app into many small services before one simple app has been tested.
- Caching before traffic. Caching means keeping ready copies of data so pages load faster. It solves a speed problem you don't have yet.
- Code for features that don't exist. Flexible "frameworks" built for future needs nobody has confirmed.
- New tools from last week's article. Each one adds something to learn, update and fix.
Each choice looks smart alone. Together, they turn a two month product into a ten month one.
Should a startup use microservices or a monolith?
Start with a monolith.
A monolith is one application that holds all the parts of your product. Microservices split the product into many small applications that talk to each other over the network.
Microservices help very large teams. For a startup, they multiply the work: more servers, more connections that can fail, more places to look when something breaks.
Software expert Martin Fowler wrote that almost all the successful microservice stories started with a monolith that got too big and was broken up. Systems built as microservices from scratch, he added, almost always ended up in serious trouble (Fowler, 2015).
Build one clean application first. Split it later, only if growth forces you to.
What is YAGNI, and how does it help?
YAGNI stands for "You Aren't Gonna Need It". It is a rule from Extreme Programming, a way of working that many software teams use: don't build something now because you think you will need it later (Fowler, 2015).
Before building anything, ask three questions:
- Does a real user need this today? Not "might need", today.
- Does it solve a business problem or bring in money?
- What breaks if we skip it for now? If the answer is "nothing", skip it.
If a feature fails all three, put it on a later list. You lose nothing, because you can always build it when the need is real.
University project vs market reality: what's different?
| University project | Market reality | |
|---|---|---|
| Who grades it | A jury | Paying customers |
| What earns points | Showing knowledge | Solving a problem fast |
| Complexity | A sign of effort | A cost the customer pays |
| Timeline | Months of planning | Weeks to a first version |
| Success | A good mark | Customers who come back |
The left column is how you can fail without noticing for two years, then discover nobody wanted what you built.
When is complexity worth it?
Simple does not mean sloppy. Some parts of a product deserve full care from day one:
- Security. The server checks prices and permissions, never the browser.
- Backups. Daily, automatic and tested.
- Money records. Never edited, only corrected with new entries. I explain why in never edit a money record.
- The data model. How information is stored is hard to change later.
Put your engineering effort there, and keep everything else simple. I explain what a good simple product looks like in minimum viable is not minimum effort.
Why does this matter in Algeria?
Many Algerian graduates turn their final year project, the PFE (projet de fin d'études), into their first startup. That is a good start: the idea has been studied and the student knows the subject.
But the PFE was built for a jury. Turning it into a product means removing what impressed the jury and keeping what helps the customer.
Algerian customers also judge fast. Most will test your product on a mid range phone, on a connection that drops. A simple app that loads quickly wins over a clever one that hangs.
I explain how to keep costs down in why expensive apps die before launch. And what changes between a demo and a real product in prototype vs production.
What mistakes do new founders make?
- Designing for millions before having ten users. Build for the users you have.
- Choosing tools to look smart. Choose tools you can fix at 2am.
- Building features "for later". Apply YAGNI.
- Skipping security and backups to save time. Keep simple and safe together.
- Measuring progress in code written. Measure it in customers who come back.
What should you do this week?
- Today: list every part of your system. Mark the ones no current user needs.
- This week: for each feature on your plan, ask the three YAGNI questions.
- This week: if your app is split into many services with few users, consider merging it into one.
- Before launch: confirm backups, server side checks and safe money records.
- Every week after: add complexity only when a real user problem asks for it.