Embracing the 3-Month Rule: A Pragmatic Approach to Non-Scalable Solutions
In the entrepreneurial landscape, there’s a well-recited mantra from Paul Graham: “Do things that don’t scale.” Yet, one critical aspect often overlooked is how to effectively apply this principle in software development. After eight months of constructing my AI podcast platform, I have developed a technical framework to navigate the realm of non-scalable solutions: the 3-Month Rule. This straightforward guideline allows any unscalable workaround to survive for three months; at the end of this period, we assess whether it warrants further investment or should be scrapped.
As engineers, our instinct tends to lean towards building scalable architectures right from the start—think design patterns, microservices, and distributed systems. However, this approach often represents a mindset suited for larger organizations, where scalability is a primary concern. In the startup context, focusing on scalable solutions can lead to unnecessary expenses and delayed progress. My 3-Month Rule compels me to embrace simplicity, facilitating quicker iterations while revealing the genuine needs of my users.
Current Simplified Infrastructure Hacks and Their Unexpected Benefits
1. Consolidation on a Single Virtual Machine
For just $40 a month, my entire application, including the database and web server, operates on a single VM. While this setup lacks redundancy, it has provided invaluable insight into my actual resource demands. In only two months, I have gleaned more important data about RAM usage than any complex planning document could have offered. Should a crash occur—something that’s happened a couple of times—I gain real-time insights into failures, dispelling my initial expectations of what might go wrong.
2. Hardcoded Configurations for Simplicity
Instead of employing dynamic configuration files, I utilize hardcoded constants scattered throughout my codebase. Modifying parameters such as pricing or maximum users necessitates redeployment, which may seem inefficient, but the advantages are clear. The ability to quickly search my entire codebase for any configuration value is invaluable, and every change is meticulously tracked through version control. This straightforward cadre of constants has proved to be more efficient than spending a week developing a configuration service for the few changes I have made.
3. Using SQLite in a Production Environment
Surprisingly, I have opted for SQLite in my multi-user application, which currently requires only 47MB of database space. It efficiently handles up to 50 users concurrently, allowing me to discern my
