Embracing the 3-Month Rule: A Pragmatic Approach to Development

In the startup world, there’s a widely recognized principle coined by Paul Graham: “Do things that don’t scale.” While many acknowledge this advice, few delve into the practical implementation, especially within the realm of coding. Having spent the last eight months developing my AI podcast platform, I’ve devised a straightforward framework that I refer to as the “3-Month Rule.” Each unscalable approach receives a trial period of three months; after this, it either solidifies its worth and evolves into a full-blown solution, or it is discarded.

Understanding the startup Paradigm

As engineers, our instinct often drives us towards crafting scalable solutions from the outset, employing intricate design patterns and architectural frameworks to manage vast user bases. However, this approach can lead to a significant disconnect in a startup setting. Focusing on scalability too early can result in investing time and resources into problems that may never manifest.

My 3-Month Rule compels me to prioritize simplicity and speed, allowing me to produce “quick and dirty” code that actually delivers functionality while revealing what users genuinely need.

Noteworthy Infrastructure Strategies

Here are some of my current infrastructural choices and the rationale behind each:

1. Single VM Deployment

Everything, from the database to the web server, operates on a single $40/month virtual machine, devoid of redundancy and dependent on manual local backups.

Why is this effective? In just two months, I gained insights into my actual resource requirements that formal capacity planning could never provide. My platform, heavily reliant on AI, topped out at 4GB of RAM. The Kubernetes configuration I nearly pursued would have required managing clusters that weren’t even necessary.

When failures occur—and they have, twice—I receive invaluable feedback about the actual points of failure, which often surprises me.

2. Hardcoded Configurations

Instead of employing configuration files or environment variables, I’ve opted for hardcoded constants, such as:

python
PRICE_TIER_1 = 9.99
MAX_USERS = 100

This method may seem rudimentary, but it allows me to quickly search the entire codebase for configuration values and maintain a clear history of changes via version control. The time I would have spent developing a dedicated configuration management service—over 40 hours—proved unnecessary for the few modifications I’ve made.

3. Utilizing SQLite in Production

Yes