Embracing the 3-Month Rule: A Technical Approach to Non-Scalable Solutions

In the startup ecosystem, Paul Graham’s timeless advice to “do things that don’t scale” often resonates with entrepreneurs and innovators. Yet, many grapple with how to actually apply this principle within the realm of software development. Drawing from my experience building an AI podcast platform over the last eight months, I have crafted a framework that allows for the strategic implementation of non-scalable solutions: the 3-Month Rule. This framework stipulates that any unscalable hack should be given a trial period of three months. At the end of this period, either the idea is validated and developed further, or it’s discarded.

While we, as engineers, tend to focus on creating scalable architectures—think microservices, distributed systems, and intricate design patterns—this approach is often better suited for larger organizations. In the startup world, overly ambitious scalability can lead to wasted resources by tackling future concerns rather than current needs. By employing the 3-Month Rule, I prioritize straightforward, even “imperfect,” coding practices that deliver tangible results and provide insight into user demands.

My Current Infrastructure Hacks: Learning from Non-Ideal Solutions

1. Consolidated Infrastructure on a Single VM

For just $40 a month, my entire platform operates on one virtual machine housing everything from the database to the web server. While this may seem reckless with zero redundancy and manual backups, the insights gained are invaluable. I’ve learned more about my resource requirements in two months than traditional capacity planning could ever reveal.

Through real-time data analysis during system crashes, I discovered that the “AI-heavy” platform only peaks at 4GB of RAM. The overly complex Kubernetes setup I nearly implemented would have only served to manage idle containers.

2. Hardcoded Configurations for Simplicity

Instead of relying on configuration files or environment variables, I’ve hardcoded parameters directly into the code. For example:

python
PRICE_TIER_1 = 9.99
MAX_USERS = 100

This configuration method, while seemingly outdated, allows me to quickly search my codebase for any values and keeps track of changes through version control. In three months, I’ve only modified these values a handful of times, saving me from the hours of engineering time that a configuration service would require.

3. Utilizing SQLite in Production

Surprisingly, my multi-user application operates smoothly on SQLite, maintaining