Embracing the 3-Month Rule: A Practical Framework for Unscalable Solutions in Tech
In the tech world, everyone is familiar with Paul Graham’s famous saying: “Do things that don’t scale.” However, few delve into how to put this advice into action, especially in the realm of coding. After spending the last eight months creating my AI podcast platform, I’ve formulated a simple yet effective framework to guide my development process: every unscalable solution is given a lifespan of three months. At the end of that period, it either proves its worth and gets properly developed, or it gets retired.
As engineers, we often feel compelled to design scalable solutions from the outset—creating intricate systems using design patterns, microservices, and distributed frameworks to accommodate millions of users. However, this mindset can sometimes be a pitfall, particularly in the startup arena where ‘scalable’ often translates to ‘expensive procrastination.’ My three-month rule encourages me to prioritize simplicity, enabling me to produce straightforward code that not only launches but also provides valuable insights into user needs.
Current Infrastructure Hacks: Innovative Strategies That Yield Insight
1. Consolidating Everything on a Single Virtual Machine
I’m operating my database, web server, background jobs, and caching all on one $40-a-month VM. While it lacks redundancy and relies on manual backups, this approach has provided invaluable insight into my resource utilization over the past two months. I discovered that my platform, which I initially considered “AI-heavy,” peaks at just 4GB of RAM. The elaborate Kubernetes architecture I almost put in place would have meant managing idle containers.
When the system encounters crashes (which have happened twice), I gain precise data on the failure points—often revealing surprises along the way.
2. Using Hardcoded Configurations
With key parameters such as pricing and user limits hardcoded directly into the code, any changes require a redeployment. While this may seem primitive, the efficiency it affords is remarkable. I can quickly search through my codebase for any configuration value, tracking every change through version control. Over three months, I’ve made just three updates—taking a mere 15 minutes to redeploy versus the potential 40 hours of building a configuration service.
3. Deploying SQLite in Production
Yes, I’m utilizing SQLite for a web application that serves multiple users. The entire database is only 47MB, and it effortlessly supports 50 concurrent users. This experience has
