Embracing the 3-Month Rule: A Pragmatic Approach to Non-Scalable Solutions
In the world of startup development, there’s a popular recommendation from startup guru Paul Graham: “Do things that don’t scale.” While this advice resonates with many entrepreneurs, the practical implementation of it—particularly in programming—is often overlooked. After eight months of building my AI podcast platform, I’ve crafted a simple yet effective framework that I call the “3-Month Rule.” This approach has transformed my understanding of coding for early-stage ventures.
The Essence of the 3-Month Rule
For startups, the impulse to prioritize scalability can lead to unnecessary complications and waste. As developers, we are conditioned to create elegant solutions that are capable of handling vast amounts of traffic and data. However, in a startup environment, investing time in scalable solutions can feel like procrastination—it’s like optimizing for an audience that doesn’t yet exist. My 3-month rule encourages me to embrace simpler coding practices that yield results quickly and provide vital insights into user needs.
Practical Infrastructure Hacks That Yield Big Insights
1. Single VM Setup
I’ve consolidated my entire system—database, web server, background jobs, and caching—on a single virtual machine costing just $40 a month. This setup might seem reckless due to its lack of redundancy and reliance on manual backups, yet it has proven invaluable. In just two months, I’ve gained a clear understanding of my resource requirements. My platform, which I initially presumed would be memory-intensive, only peaks at 4GB of RAM. The complex Kubernetes configuration I was about to implement would have been a waste, as I now have concrete data on actual failures—insights that I never anticipated.
2. Use of Hardcoded Configuration
In my code, configuration values such as pricing tiers and user limits are hardcoded. While this approach simplifies the deployment process—requiring only a redeployment when changes occur—it also grants me the ability to quickly trace any configuration alterations through my version control history. Instead of investing a week in developing a sophisticated configuration service, I can modify essential constants in mere minutes.
3. Utilizing SQLite for Production
I’ve adopted SQLite for my multi-user web application, and it operates seamlessly with a 47MB database capacity, easily supporting up to 50 concurrent users. This decision allows me to efficiently manage my predominantly read-heavy data access patterns. A shift to a more complex database like Postgres would have necessitated preparations
