Embracing the 3-Month Rule: A Practical Approach to Non-Scalable Solutions in Software Development
In the world of software development, the advice from Paul Graham resonates with many: “Do things that don’t scale.” However, the challenge arises when it comes to the actual implementation of this principle, especially when coding. As I embark on my journey of building an AI podcast platform, I’ve crafted a straightforward yet effective framework: every unscalable hack is given a lifespan of three months. If it proves its worth, it gets refined; if not, it is discarded.
Rethinking Scalability
As engineers, our training often emphasizes creating scalable solutions from the outset. We immerse ourselves in sophisticated design patterns, contemplate robust microservices, and dream of creating systems that can support millions of users. However, this mindset can be counterproductive in a startup environment where premature scaling can often lead to wasted resources. My three-month rule compels me to produce straightforward, quick-to-ship code that provides clear insights into users’ actual needs.
Key Infrastructure Hacks and Their Strategic Value
1. Unified VM Infrastructure
Currently, my entire system—database, web server, background tasks, and caching—resides on a single $40/month virtual machine. While this setup lacks redundancy and relies on manual backups, it has been a revelation. In just two months, I’ve acquired invaluable insights into my resource requirements. Initially, I was tempted to deploy a complex Kubernetes architecture, but it turns out that my platform’s peak usage is just 4GB of RAM. The crashes have provided unexpected lessons about where my actual vulnerabilities lie, often deviating from my initial assumptions.
2. Simplified Configuration Management
My approach to configuration is decidedly low-tech: hardcoded values scattered throughout my codebase. While conventional wisdom would advocate for using configuration files or environment variables, this method allows me to efficiently track changes, as each modification is logged in my Git history. In three months, I’ve altered configuration settings only three times, saving me countless hours of engineering effort that would have gone into building an elaborate management system.
3. Employing SQLite in Production
I chose SQLite for my multi-user web app, and it has proven surprisingly effective. With a compact database size of 47MB, it seamlessly accommodates 50 concurrent users. This choice has illuminated my access patterns, revealing a 95% read to 5% write ratio. Had I opted for a heavier database system like
