Embracing the 3-Month Rule: A Practical Approach to Rapid Development

In the world of software development, the legendary advice from Paul Graham resonates: “Do things that don’t scale.” Yet, there seems to be a lack of discussion on how this translates into practical coding strategies. After dedicating eight months to developing my AI podcast platform, I discovered a straightforward approach that I like to call the “3-Month Rule.” This framework allows me to test unscalable hacks for a limited time, after which I assess their viability for development. If they prove their worth, they are transitioned into a more polished version; if not, they are phased out.

As engineers, we often find ourselves gravitating towards scalable solutions right from the start—microservices, distributed systems, and intricate architectures designed to serve potential high user counts. However, this mindset can lead to time wasted on complexities that may never be needed, particularly in a startup environment. My 3-Month Rule has encouraged me to develop simpler, more straightforward code that provides valuable insights into user needs rather than chasing hypothetical issues.

Ingenious Infrastructure Hacks That Work

Here are some methods I’ve employed that may seem unconventional but offer profound benefits.

1. Consolidated Systems on One Virtual Machine (VM)

I host my database, web server, background jobs, and Redis all on a single $40/month VM, with no redundancy and manual backups to my local machine. While this may seem risky, it drastically improved my understanding of resource requirements. Within two months, I discovered that my platform peaked at 4GB RAM usage. Had I set up a complex Kubernetes environment, I would have wasted time managing unnecessary resources.

When my VM does crash—something that has occurred twice—I gain real-time data about failure points. Invariably, they were not what I anticipated.

2. Simplistic Hardcoded Configuration

By hardcoding configuration values directly into my codebase, such as pricing tiers and maximum users, I eliminate the complications of dealing with external configuration files or environment variables. This approach, while seemingly outdated, allows me to quickly locate any configuration value and track changes through Git history. With minimal adjustments in three months, the time spent redeploying is inconsequential compared to the extensive engineering work a dedicated configuration service would have required.

3. Leveraging SQLite for Production Use

Yes, I am employing SQLite as the database for a multi-user web application, and it efficiently handles 50 concurrent