Embracing the 3-Month Rule: A Practical Approach for Startups

In the entrepreneurial world, advice from thought leaders like Paul Graham often circulates widely. One piece of wisdom that resonates with many is “Do things that don’t scale.” But how exactly can this principle be applied to the realm of coding?

After working on my AI podcast platform for the past eight months, I’ve formulated a straightforward framework that I like to call the “3-Month Rule.” It operates on a simple premise: every unscalable solution receives a trial period of three months. At the end of this timeframe, we assess whether the method has proven its worth and can be expanded, or whether it’s time to move on and find a better way.

The Challenge of Scalability

As engineers, we often come into the field with a mind focused on scalability. We’re trained to think in terms of sophisticated design patterns, complex microservices, and robust distributed systems, all intended to serve millions of users. However, this mindset frequently becomes a hindrance in the startup environment, where the emphasis on scaling can lead to unnecessary delays and expenses.

When you’re trying to optimize for users who don’t yet exist, you risk overcomplicating solutions for problems that might never arise. The 3-Month Rule encourages me to create straightforward, albeit imperfect solutions that can be deployed quickly. This method enables me to gather genuine feedback and insights on what users truly require.

Real-World Applications of My Infrastructure Hacks

1. Consolidated Operations on a Single VM

I run my entire platform—including the database, web server, and background services—on a single $40/month virtual machine. While it may seem unwise without redundancy or automated backups, this approach has provided invaluable insights into my actual resource needs over two months. I’ve learned that my platform, which I expected to be resource-intensive, peaks at just 4GB of RAM. Attempting to set up a complex Kubernetes architecture would have resulted in managing empty containers rather than meeting any genuine demands.

2. Simplified Configuration Management

My system employs hardcoded configuration values like:

plaintext
PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"

While this method may not be conventional, it offers the advantage of easy tracking and rapid adjustments. I can