Embracing Unscalable Solutions: The 3-Month Rule for Rapid Learning in Development
In the world of startups, the age-old advice from Paul Graham—“Do things that don’t scale”—often hangs in the air, inspiring many to take the plunge into the chaotic waters of innovation. Yet, a critical gap remains: how do we effectively translate this advice into actionable coding practices?
Over the past eight months, while crafting my AI podcast platform, I’ve established a pragmatic framework that I call the “3-Month Rule.” Essentially, any solution that doesn’t scale gets a trial period of three months. During this time, it must demonstrate its value or face elimination. This approach has transformed my development process, allowing me to focus not on perfecting scalability but on understanding real user needs.
The Reality of startup Engineering
As engineers, we are often trained to prioritize scalable solutions right from the outset. Concepts like microservices, distributed systems, and complex architecture fill our heads with ideas geared towards handling overwhelming user loads. However, in the startup realm, investing in scalability too early can lead to inefficiencies and wasted resources. The reality is that often, you’re building for a user base that doesn’t even exist yet.
With my 3-month rule, I compel myself to produce straightforward, albeit “imperfect,” code that I can deploy quickly. This approach has fostered a more profound understanding of my users’ actual requirements.
My Pragmatic Infrastructure Hacks
1. Consolidating Everything on a Single Virtual Machine
Operating my entire infrastructure—from the database to the web server, along with background processes—on a singular $40/month VM may seem risky, but it’s bearing fruit. I’ve observed real resource needs that would have eluded any traditional capacity planning. Initially, I contemplated a complex Kubernetes architecture only to realize that my platform’s peak resource requirement hovers around 4GB of RAM. Any downtime provides invaluable insights into failure points, often contrary to my predictions.
2. Directly Hardcoding Configuration Settings
My codebase features constants peppered throughout, including set pricing and user limits. While this may seem simplistic, it offers an unexpected advantage: rapid searches for configuration values and easy version control tracking. I’ve redefined variables a mere three times in the last three months—a stark contrast to the time-consuming process of setting up a dedicated configuration service.
3. Utilizing SQLite in Production
Running SQLite for a multi-user application might
