Embracing the 3-Month Rule: A Pragmatic Approach to Development in Startups
In the realm of startups, the journey of development often diverges from the traditional wisdom of scalability. While Paul Graham famously advises entrepreneurs to “Do things that don’t scale,” the nuances of this principle in coding are less frequently discussed. After eight months of building my AI podcast platform, I’ve devised what I call the “3-Month Rule” to effectively implement this philosophy.
The essence of my framework is simple: any unscalable workaround or hack is granted a lifespan of three months. Within this period, the hack must either prove its value and evolve into a robust solution or be discarded altogether.
The Dilemma of Scalability in Startups
As developers, we often gravitate towards creating solutions that are scalable from the onset. The allure of polished architecture, complete with design patterns and microservices, is strong. However, in the startup landscape, focusing on scalability can lead to costly delays, optimizing for users that may never materialize. By applying my 3-month rule, I prioritize simple, functional coding practices that yield immediate insights into user needs while facilitating rapid iteration.
Current Infrastructure Strategies: What I’ve Learned
1. Single VM Simplicity
Everything from my database to the web server is hosted on a single $40/month virtual machine, devoid of redundancy and manual backup practices. This approach has yielded invaluable lessons about my actual resource requirements in just two months. I’ve found that my AI platform’s peak usage is a modest 4GB of RAM, debunking the need for a complex Kubernetes setup aimed at managing empty containers.
Every crash teaches me something new—it’s surprising what breaks is often not what I anticipated.
2. Hardcoded Configuration
In my codebase, configuration values are hardcoded directly. This might seem counterproductive, but it allows rapid changes with minimal overhead. With all configurations visible and trackable in git history, modifications are straightforward and require merely redeployment. In the past three months, I’ve adjusted these constants only three times—saving me significant development hours.
3. SQLite Usage
Choosing SQLite for a multi-user application may seem unconventional, but it works wonders for my current needs. With a database size of only 47MB, I’ve confidently managed 50 simultaneous users. Understanding my access patterns—95% reads against 5% writes—has clarified my needs. Had I opted for a more complex solution
