Embracing the 3-Month Rule: A Framework for Growing with Your Startup

In the startup world, the mantra “Do things that don’t scale,” famously coined by Paul Graham, is often echoed. However, the essential steps to effectively implement this advice, particularly in the realm of software development, rarely receive attention. After dedicating eight months to the creation of my AI-centric podcast platform, I’ve established a straightforward yet profound framework: every non-scalable approach is granted a lifespan of just three months. By that time, it must either demonstrate its worth and evolve into a robust solution or face elimination.

The Reality of Engineering in Startups

As engineers, we are often shaped by the preference for creating scalable solutions from the outset. We immerse ourselves in sophisticated design patterns, intricate microservices, and distributed systems—all tailored to cater for millions of users. While these practices are certainly beneficial, they reflect the mindset typical of large enterprises.

In the environment of a startup, endlessly preparing for scalability can equate to costly inertia. We may find ourselves refining processes and addressing issues for users who are yet to materialize. My 3-month rule compels me to embrace simpler, more immediate code—a shift that not only allows me to launch quickly but also helps me discern the actual needs of my users.

My Pragmatic Infrastructure Hacks

Let’s delve into some of the unconventional solutions I’ve employed, which reveal a more astute approach than they might initially appear:

1. Consolidating Resources on a Single Virtual Machine

My entire stack—database, web server, background jobs, and Redis—is hosted on a single Virtual Machine (VM) costing just $40 a month, with manual backups to my local system. This might seem risky, but the insights I’ve gained over the past couple of months have overshadowed any initial misunderstanding.

I’ve quickly discovered that my application’s resource demands peak at 4GB of RAM, rendering my previous ambitions for an elaborate Kubernetes setup unnecessary. The crashes I’ve experienced have provided invaluable real-world data, offering clarity on what truly requires attention—information that often contradicted my expectations.

2. Simplified Configuration Management

With constants embedded directly into code rather than utilizing configuration files or environment variables, modifying settings means redeploying the code. This approach, while seemingly cumbersome, allows for rapid changes across the entire codebase with a simple search. Over three months, I’ve only made three pricing adjustments—an effort that took mere minutes, contrasting