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

In the fast-paced world of startups, we often hear the wisdom of Paul Graham: “Do things that don’t scale.” However, the challenge lies in translating this advice into actionable steps, particularly in the realm of software development. Over the past eight months while building my AI podcast platform, I have adopted a straightforward yet effective framework: every unscalable solution is granted a lifespan of three months. After this period, we either elevate it into a well-structured solution or let it go.

The startup Mindset: Why Scaling Early Can Be a Trap

As engineers, we are conditioned to prioritize “scalable” solutions from the very beginning. We envision sophisticated architectures involving design patterns, microservices, and distributed systems, all crafted to accommodate millions of users. However, this is often the mindset of larger companies, leaving startups with unnecessary complexities.

In a startup environment, aiming for scalability can sometimes lead to costly delays. You risk investing time in optimizing for users that don’t yet exist, tackling problems that may never materialize. My three-month rule compels me to write simple and direct code that can be implemented quickly, ultimately revealing the true needs of my users.

My Ingenious Infrastructure Hacks

Let’s dive into some of the unconventional yet effective strategies I’ve employed:

1. Consolidated Infrastructure on One VM
My entire application ecosystem, including the database, web server, and background jobs, operates on a single virtual machine costing $40/month. This setup, while devoid of redundancy and relying on manual backups, has provided invaluable insights into my resource consumption. In just two months, I learned that my platform, which I assumed required extensive resources, only peaks at 4GB of RAM. This hands-on experience has highlighted where my genuine bottlenecks lie, as opposed to managing an intricate infrastructure that might not be necessary.

2. Hardcoded Configuration for Agility
Rather than using configuration files or environment variables, I’ve opted for hardcoded constants. While this may seem primitive, it allows for rapid identification of configuration changes across the codebase. Every modification is tracked in version history, and I’ve only had to redeploy for three changes over three months—saving countless hours of engineering time that would have been spent building a complex configuration management system.

3. Utilizing SQLite in Production
I made the unconventional decision to deploy SQLite for a multi-user application