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

In the world of technology startups, the mantra “Do things that don’t scale,” popularized by Paul Graham, resonates strongly. However, the challenge often lies in how to apply this wisdom effectively, particularly in coding practices. Over the past eight months, as I’ve been developing my AI podcast platform, I’ve adopted a unique philosophy: any temporary hacks that are not designed for scalability only get three months to prove their worth. If they don’t hold up, they are discarded.

The Truth About Scalable Solutions

As engineers, we’re conditioned to dream big, crafting scalable architectures from day one to handle vast user bases with sophisticated technologies like microservices and distributed systems. While this approach suits larger organizations, in the startup arena, it can merely become an expensive delay, as we optimize for hypothetical users and problems that may never materialize. My 3-month rule compels me to create straightforward, sometimes less-than-ideal code that is functional and insightful, enabling me to decipher the actual needs of my users.

My Innovative Infrastructure Hacks

Here are some of my current infrastructure tactics that, while seemingly simplistic, have proven to be strategically sound:

1. Single VM Setup

I have everything—database, web server, background tasks, and caching—operating from one $40/month virtual machine. This setup lacks redundancy and involves manual backups.

Why is this insightful rather than reckless? In just two months, I’ve gained more understanding of my resource requirements than I would from extensive planning documentation. My platform, initially thought to be resource-intensive, requires a maximum of 4GB RAM, meaning the complex Kubernetes architecture I nearly implemented would have been needlessly managing empty resources. Each time the system crashed, I learned invaluable lessons about the actual points of failure.

2. Hardcoded Configuration Settings

Rather than utilizing configuration files or environment variables, I encapsulate constants like price tiers and user limits directly within the code.

This method might seem archaic, but its efficiency lies in its simplicity. I can scan my entire codebase for changes swiftly, and any adjustments are documented through version control. Instead of embarking on the week-long process of constructing a configuration service, I have invested a mere 15 minutes redeploying for a handful of value changes.

3. SQLite for Production

Utilizing SQLite for my multi-user web application, which only occupies 47MB