Embracing the 3-Month Rule: A Pragmatic Approach to Unscalable Development
In the world of startups, the phrase coined by Paul Graham, “Do things that don’t scale,” often echoes in the ears of aspiring entrepreneurs. Yet, the practical application of this advice within the realm of software development remains a rarity. As I embark on my journey of building an AI podcast platform, I’ve honed a straightforward framework that has proven invaluable: every unscalable hack has a life expectancy of just three months. After this period, each must either demonstrate its worth through tangible results or be discarded.
As software engineers, we are typically conditioned to prioritize scalability from the outset. Concepts like design patterns, microservices, and distributed systems are integral to creating applications meant to serve millions of users seamlessly. However, in the startup domain, focusing solely on scalable solutions can often lead to unnecessary expenses and delays. My three-month rule compels me to produce straightforward, albeit sometimes inelegant, code that actually implements features and provides insight into user needs.
My Experiments: Practical Hacks that Drive Meaningful Learning
1. Unified VM Architecture
For just $40 a month, I’ve consolidated my database, web server, background jobs, and caching into one virtual machine. This setup is not without its risks—zero redundancy and manual backups. Nevertheless, this arrangement has granted me invaluable insights into my resource requirements far beyond what any capacity planning document could have provided. It turns out my platform’s resource usage peaks at a mere 4GB of RAM. The intricate Kubernetes infrastructure I was tempted to build would have involved managing idle containers.
When the system experiences its inevitable crashes—there have been two so far—I glean significant data about failures, and interestingly, they are never what I anticipated.
2. Simplified Configuration Management
Instead of relying on configuration files or environment variables, I’ve opted for hardcoded values that are scattered throughout my code. This might seem outdated, but it’s remarkably practical. A moment’s glance allows me to quickly locate and track changes to any configuration value through Git history. Since I’ve only modified these parameters three times in the last three months, a simple redeployment takes merely 15 minutes compared to an estimated 40 hours it would take to build a dedicated configuration service.
3. Leveraging SQLite for Production Use
Despite its reputation, SQLite is the backbone of my multi-user web application, supporting 50 concurrent users effortlessly with a database size of
