Embracing the 3-Month Rule: A Pragmatic Approach to Non-Scalable Solutions in Software Development
In the entrepreneurial world, wisdom often comes from unexpected sources. Paul Graham’s advice to “do things that don’t scale” frequently echoes in startup circles, but the real challenge lies in implementing this philosophy in technical environments. After eight months of developing my AI podcast platform, I have devised a straightforward yet effective framework: allow every non-scalable solution to operate for three months. At the end of this period, the solution either proves its worth and is refined, or it is discarded.
As engineers, we’re trained to aspire to scalable architectures from day one—think microservices, distributed systems, and other robust solutions designed to handle high traffic. However, this mindset can lead to procrastination in startups, wherein we optimize for theoretical users rather than the actual ones in front of us. My 3-month rule compels me to utilize straightforward, even “imperfect,” code that can be quickly deployed. This approach enables me to learn what my users truly need.
Current Infrastructure Hacks: Smart Techniques for Immediate Insights
1. Unified VM Hosting
Currently, my entire infrastructure—from the database to web servers and background jobs—operates on a single $40/month virtual machine. While it lacks redundancy and requires manual backups, this simplicity has provided invaluable insights into my resource usage. Within two months, I’ve discovered that my “AI-centric” platform only peaks at 4GB of RAM. Any intricate arrangements, like a Kubernetes setup, might have been wasted on empty containers had I pursued them prematurely. Each time the server crashes, I gain tangible feedback on what malfunctioned—often contrary to my expectations.
2. Hardcoded Configuration
Instead of using configuration files or environment variables, I have hardcoded critical values, such as pricing tiers and user limits, directly into the code. Redeploying is necessary to change these values, yet this setup grants me a unique advantage: I can swiftly search my codebase for any configuration value, facilitating efficient version tracking through Git. Over the past three months, I’ve adjusted these configurations only three times, resulting in a mere 15 minutes of redeployment compared to an estimated 40 hours that a dedicated configuration service would have required.
3. SQLite for Database Management
Yes, SQLite is my chosen database for a multi-user application. With a modest database size of 47MB, it comfortably
