Embracing the 3-Month Rule: A Practical Approach to Non-Scalable Solutions
In the ever-evolving world of technology, the mantra by Paul Graham to “do things that don’t scale” is often echoed yet rarely dissected, especially in the realm of coding. After spending eight months developing my AI podcast platform, I’ve established a straightforward framework to effectively implement this advice: every unscalable hack is allowed a trial period of three months. If a solution doesn’t prove its worth within that timeframe, it’s time to let it go.
The startup Mentality: Choosing Learning Over Scale
As engineers, we’re often conditioned to think about building scalable solutions right from the onset. We aim for meticulous architecture capable of supporting millions of users, drawing on design patterns, microservices, and distributed systems. This mindset, while valuable in larger companies, can lead startups down a path of costly procrastination—focusing on potential users who may never materialize and crafting elaborate solutions for problems that don’t exist.
My 3-month rule ensures I focus on deploying simple, straightforward code that actively engages with users, providing critical insights into their actual needs.
Current Infrastructure Hacks: A Smarter Approach
1. Consolidating Resources on a Single VM
Instead of complicating my infrastructure, I’ve chosen to run everything—from the database to the web server—on a single $40-per-month virtual machine. This setup may lack redundancy and rely on manual backups, but it has taught me more about my resource requirements in two months than any written capacity plan could. The results? My platform usually operates with just 4GB of RAM—a far cry from the complex Kubernetes architecture I initially envisioned.
When crashes occur (yes, twice so far), they reveal unexpected points of failure, providing real feedback that helps refine my approach.
2. Hardcoded Configuration Values
My configuration is straightforward: constants such as pricing tiers and user limits are hardcoded within the files. While this may seem primitive compared to using dedicated configuration services, it enables rapid detection of changes through a simple search, and any adjustment requires just a quick redeployment. In three months, I’ve only changed prices thrice—saving significant engineering time while ensuring rigorous version control.
3. Utilizing SQLite for Operations
Surprisingly, I’m relying on SQLite to manage my multi-user web application. With a database size of just 47MB, it supports 50 concurrent users efficiently. This experience
