Embracing the 3-Month Rule: A Practical Approach to Engineering in Startups
In the startup world, the mantra “do things that don’t scale” is often echoed, most famously by Paul Graham. Yet, the challenge lies in applying this principle, especially when it comes to coding. After eight months of building my AI podcast platform, I’ve developed a straightforward framework to navigate this daunting task: every hack that doesn’t scale is given a lifespan of just three months. Following this period, I evaluate whether it adds value and requires proper development or if it’s time to phase it out.
As engineers, our instinct is to create “scalable” solutions from the get-go. We often design complex infrastructures—leveraging microservices, distributed systems, and other advanced architectures—to accommodate future users. However, in the startup arena, pursuing scalability too early can lead to costly delays, optimizing for hypothetical users and problems that may never arise. By adhering to my three-month rule, I focus on writing straightforward, albeit “imperfect,” code that gets deployed, helping me truly understand user needs.
Current Infrastructure Hacks: A Deep Dive
1. One VM to Rule Them All
By running my entire platform—database, web server, background jobs, and caching—on a single, economical $40/month virtual machine, I’ve gained invaluable insights into my actual resource requirements. With zero redundancy and manual backups, I quickly discovered that my supposedly “AI-heavy” platform rarely exceeded 4GB RAM. Instead of building a complex Kubernetes environment, I can directly observe what breaks during downtime, which is often a surprise.
2. Hardcoded Configuration Values
In my codebase, every configuration value—like pricing tiers and user limits—is hardcoded within the files. I’ve opted against separate config files or environment variables. While some may see this as a downside, I benefit from the simplicity: a quick search across my codebase for any configuration can be done in seconds. Each price adjustment is tracked in version control, allowing for efficient management. Spending 15 minutes redeploying is far more efficient than the hours it would take to implement a dedicated configuration service.
3. SQLite for Production Use
Yes, you read that right—I’m employing SQLite to handle my multi-user web application, a database that currently weighs in at a mere 47MB. Remarkably, it supports 50 concurrent users seamlessly. Through usage tracking, I found that my app
