Embracing the 3-Month Rule: A Pragmatic Approach to Unscalable Solutions
In the world of startups, the mantra “Do things that don’t scale,” popularized by Paul Graham, is widely recognized yet often overlooked in practice. The challenge lies in understanding how to effectively implement this philosophy, particularly in the realm of software development.
Having spent the last eight months cultivating my AI podcast platform, I’ve arrived at a straightforward yet powerful framework: any unscalable hack has a lifespan of just three months. After this period, it must either prove its worth and evolve into a more robust solution or be discarded entirely.
The start-up Perspective: Rethinking Scalability
As engineers, we are often conditioned to design scalable systems from the outset. Concepts like microservices, distributed architectures, and complex design patterns can dominate our thinking. However, in the startup environment, pursuing scalable solutions too early often results in wasted effort—essentially optimizing for users who haven’t yet arrived and addressing issues that may never materialize.
My 3-month rule encourages me to favor straightforward, even “messy” code, which allows for rapid deployment and invaluable insights into user needs.
My Current Infrastructure Strategies and Their Value
1. Consolidated Resources on a Single VM
I run my database, web server, background jobs, and caching all on a single virtual machine costing just $40 per month. This choice prioritizes simplicity over redundancy. While manual backups are stored locally, the knowledge I’ve gained about my actual resource utilization is priceless. For instance, my initial assumptions about needing extensive resources have proven incorrect; my platform typically peaks at around 4GB of RAM. When crashes occur, they provide real data about what truly fails—often surprising insights.
2. Hardcoded Configuration for Agility
In my code, configuration values like pricing tiers and user limits are hardcoded rather than stored in separate files or environment variables. This approach allows me to quickly search for any parameter using simple commands. Since I’ve only made configuration changes a few times, the time invested in redeploying these changes is minuscule compared to the hours I would have devoted to developing a complex configuration service.
3. Running SQLite for a Multi-User Application
Despite being a web app that handles multiple users, I’ve opted for SQLite as my database solution. Surprisingly, it’s been able to sustain 50 concurrent users effortlessly. Analyzing my data access patterns revealed that
