5 MVP mistakes that get expensive later
An MVP isn't "build it badly to build it fast." It's a choice: what to keep, what to defer. The problem is that some "deferred" decisions can't be added later without rebuilding half the system. Here are five such traps.
1. Not thinking about authorization early
"There's only one client, we don't need permissions" sounds reasonable. But the moment a second one shows up, it turns out authorization runs through the entire system: database queries, API methods, notification logic. Adding it later means rewriting almost everything.
The minimum worth laying down from the start: a user model, record ownership, and basic role separation. You don't need full RBAC — just a skeleton you can add detail to later.
2. Hardcoding business rules directly in code
A 10% fee, a 3-day processing time, a 5 MB max file size — if these are numbers baked into the code, the first change requires a deploy. Business rules change by nature.
Move configurable parameters into a config file or the database. It takes an extra hour during development but saves days on every subsequent change.
3. A monolithic structure that can't be split
An MVP doesn't need to be microservices — but the code should be organized so modules can be split apart when needed. If order, notification and billing logic is all tangled together, any change risks breaking everything else.
You don't need a perfect architecture from day one. You need a reasonably clear boundary between domains: separate modules, services, or at least folders with a clear responsibility.
4. Ignoring the data structure
A database schema is one of the most expensive artifacts to change. Adding a column is easy; dropping or renaming one is hard; changing a data type is painful. Spend time designing it before the first migration.
Common mistakes: storing several values in one comma-separated field, using strings where numbers belong, ignoring indexes. All of this works fine at small scale and breaks as you grow.
- Normalize your data — don't duplicate what a JOIN can get you
- Add indexes for fields you filter by often
- Don't store state as a free-form string — use an enum or a separate table
- Plan for soft deletes upfront if deleted data might be needed later
5. Not accounting for the cost of scaling
Synchronous file processing inside an HTTP request, sending email directly from a controller, heavy uncached queries — all of this goes unnoticed with 10 users and becomes a problem at 1000.
You don't need to build infrastructure for a million users right away. But you should know where your system's bottlenecks are, and leave room to add a queue, a cache, or a CDN without rewriting the logic.