Embracing the 3-Month Rule: A Practical Approach to Unscalable Solutions
In the tech world, one maxim often echoes from the mouth of renowned entrepreneur Paul Graham: “Do things that don’t scale.” While we frequently hear this in discussions about startup methodologies, the challenge lies in translating it into actionable strategies, particularly in software development. After eight months of developing my AI podcast platform, I have crafted a straightforward framework that has proven indispensable: every unscalable solution is given a three-month trial. At the end of that period, each approach must either demonstrate its value and be upgraded to a robust solution or be discarded.
A New Perspective on Scalability
Engineers often feel pressured to create scalable solutions right from the outset. The allure of elegant design patterns, microservices architectures, and distributed systems can cloud our judgment on what is necessary for immediate growth. However, within a startup environment, pursuing scalability too early can become costly procrastination. You risk pouring resources into problems that don’t exist yet, instead of focusing on delivering a product that meets the genuine needs of your users. My three-month rule is designed to push me toward writing clear, efficient, albeit imperfect code that not only launches but also reveals valuable insights about user behavior.
Insights from My Current Infrastructure Approach
Let’s delve into some of the unconventional infrastructure choices I’ve made and the reasoning behind them:
1. Unified Virtual Machine Setup
I run my entire platform on a single virtual machine for $40 a month, hosting my database, web server, background jobs, and more—all without redundancy. While this may appear risky, it has provided me with critical insights into my actual resource demands. For instance, I discovered that the peak usage of my “AI-heavy” platform was around 4GB of RAM, revealing that the complex Kubernetes structure I considered was unnecessary.
2. Simplistic Hardcoded Configuration
My codebase is rife with hardcoded constants, such as pricing tiers and user limits. While this approach eliminates configuration files and variables, it brings a unique advantage: the ability to quickly locate any configuration value throughout my codebase. It saves time by preventing lengthy setup processes for a configuration service, which would have been overkill given that I’ve only changed these values three times in three months.
3. Utilizing SQLite in Production
Indeed, I opted for SQLite for a multi-user application, and with a mere 47MB database, it has exhibited excellent performance, accommodating up to
