Title: The 3-Month Rule: A Pragmatic Approach to Building Unscalable Solutions
In the tech world, Paul Graham is often quoted for his timeless advice to “do things that don’t scale.” While this philosophy is frequently discussed, the implementation of such practices, particularly in coding, tends to be overlooked. After dedicating eight months to developing my AI podcast platform, I’ve established a straightforward framework I like to call the “3-Month Rule.” This approach allows any unscalable hack to thrive for precisely three months. At the end of this period, the solution either demonstrates its value and is appropriately developed, or it is discarded.
As engineers, we typically lean towards creating scalable designs from the outset. We often envision grand architectures like microservices or distributed systems that cater to millions of users. However, this mindset can lead to premature optimization, particularly in startup environments where scaling solutions may morph into costly delays. My 3-Month Rule compels me to embrace simplicity, allowing for “imperfect” code that actually gets deployed, ultimately revealing genuine user needs.
Current Infrastructure Hacks That Work
1. Unified Virtual Machine Setup
All of my operations—including the database, web server, and background jobs—run off a single $40-per-month virtual machine. I know, there’s no redundancy and I rely on manual backups to my personal system. However, this setup has proven surprisingly beneficial. In just two months, I’ve gained clearer insights into my resource requirements than I could have through any capacity planning document. My so-called resource-intensive platform peaks at merely 4GB of RAM. The complex Kubernetes infrastructure I nearly implemented would have required attention for nonexistent issues.
Whenever the system crashes—which has happened twice—I obtain valuable data about actual failure points, which are often unexpected.
2. Hardcoded Configuration Values
For configuration, I prefer hardcoded constants scattered throughout the codebase. This means deploying updates requires deploying the app, but it also allows me to track every price change and configuration adjustment through Git history. Instead of dedicating a week to create a configuration service, I’ve streamlined updates into a 15-minute redeployment process by adjusting values only three times in three months.
3. Using SQLite in a Production Environment
Yes, SQLite is the backbone of my multi-user web app, with a total database size of 47MB. Surprisingly, it accommodates 50 concurrent users effortlessly. This experience has taught me that my access patterns primarily
