Embracing the 3-Month Rule: A Technical Approach for Non-Scalable Solutions
In the tech startup world, the adage to “do things that don’t scale,” popularized by Paul Graham, resonates deeply. Yet, there is often little discussion about the practical implementation of this principle in software development. After eight months of building my AI podcast platform, I’ve formulated an effective method I like to call the “3-Month Rule.” This system allows me to pilot unscalable solutions; each one gets a three-month trial. After this period, the approach will either prove its worth and be properly structured, or it will be phased out.
As developers, our instinct is to design for scalability from the outset. We focus on sophisticated architectures like microservices and distributed systems intended to handle vast user bases. However, in the context of a startup, this mindset can be an expensive form of procrastination. We end up optimizing for potential users who may never materialize and addressing non-existent problems. By adhering to my 3-month rule, I find myself writing straightforward, and admittedly imperfect, code that actually gets deployed, providing insight into genuine user needs.
Current Strategies and Their Unexpected Benefits
1. Unified Virtual Machine Deployment
For just $40 per month, I’m running my database, web services, background jobs, and Redis on a single virtual machine. While this setup lacks redundancy and relies on manual backups, it has provided invaluable lessons on my actual resource needs in a matter of weeks. For instance, I learned that my resource-intensive platform peaks at 4GB of RAM, a far cry from the complex Kubernetes configuration I initially considered.
When my system crashes (which has occurred a couple of times), I gain real data about failure points—often surprising and unanticipated.
2. Simplified Configuration Management
Instead of using configuration files or environment variables, I’ve opted for hardcoded constants scattered throughout my codebase. Adjusting parameters requires a quick redeployment, which has only been necessary three times in the last three months. This method, while unconventional, allows me to easily track changes via git history and offers the advantage of rapid adjustments without the overhead of a dedicated configuration service.
3. Using SQLite for Production
Despite being a multi-user application, I’ve chosen SQLite as my database, which currently occupies just 47MB. It readily accommodates 50 concurrent users. Through this decision, I’ve discovered that my user engagement consists of
