Embracing Unscalable Solutions: The 3-Month Rule for startup Development

In the startup world, Paul Graham’s adage, “Do things that don’t scale,” is frequently cited but seldom explored in a practical context, especially within the realm of software engineering. After dedicating eight months to developing my AI podcast platform, I have devised a personal methodology that I like to call the 3-Month Rule. This approach permits me to experiment with unscalable hacks for three months, after which each solution is either validated and refined or discarded entirely.

As engineers, our instincts often lean toward creating scalable architectures from the outset. We’re trained in sophisticated frameworks, microservices, and distributed systems designed to handle vast user loads. However, this mindset can sometimes lead to wasting resources and time in early-stage startups. My 3-Month Rule challenges this conventional wisdom by compelling me to adopt straightforward, albeit suboptimal, solutions that efficiently lead me to a deeper understanding of user needs.

Current Infrastructure Approaches: Practical Yet Reflective

1. Single-VM Architecture

I’ve consolidated my database, web server, background jobs, and Redis into a single virtual machine, incurring a mere $40 a month. While this might appear reckless due to the lack of redundancy and reliance on manual backups, I’ve gained invaluable insights into my resource needs. Within just two months, I realized that my platform, which I initially assumed would require extensive resources, only peaks at 4GB of RAM. Any fears about complicated setups, like Kubernetes, have proven unwarranted, as they would have required management of empty containers instead of optimizing true utilization.

2. Hardcoded Configurations

My configurations are hardcoded within my codebase, rather than managed through complex environment files. By embedding constants directly, I can efficiently locate and modify them through simple command-line searches, dramatically reducing deployment time. This straightforward approach allows me to focus on the essentials without being bogged down by the time-consuming setup of a configuration service. In reality, I have only adjusted the configurations a handful of times over three months.

3. Using SQLite in a Multi-User Environment

Yes, my multi-user web app leverages SQLite. Contrary to the conventional wisdom of using heavier databases, my lightweight 47MB SQLite setup easily manages 50 concurrent users. This choice stems from my discovery that my usage pattern is predominantly read-oriented (95%). Thus, had I opted for a