Embracing the 3-Month Rule: A Pragmatic Approach to Unscalable Solutions in Software Development
In the fast-paced world of startups, the mantra “Do things that don’t scale,” popularized by Paul Graham, often takes center stage. However, the challenge arises when engineers attempt to apply this principle in a practical, technical context. Over the past eight months while developing my AI podcast platform, I’ve cultivated a straightforward methodology: every unscalable hack has a lifespan of exactly three months. If it doesn’t prove its worth within that time frame, it’s time for it to go.
Why the 3-Month Rule Works
As software engineers, we are often conditioned to pursue scalable solutions right from the outset. We envision complex architectures featuring design patterns, microservices, and distributed systems capable of accommodating millions of users. While these frameworks are essential for larger organizations, startups can fall into the trap of premature optimization—sacrificing speed and efficiency to cater to potential future users that may never materialize. By adhering to my 3-month rule, I focus on crafting straightforward, immediate solutions that can be implemented quickly, allowing me to truly understand my users’ needs by observing their interactions firsthand.
Current Infrastructure Hacks: Lean and Insightful
Let’s delve into some of the calculated yet unrefined infrastructure decisions I’ve made, demonstrating that simplicity can yield profound insights:
1. One Virtual Machine for Everything
Everything from the database and web server to background jobs and caching operates on a singular, budget-friendly $40/month virtual machine. While this approach lacks redundancy and relies on manual backups, it has forced me to explore my actual resource requirements in a way that traditional capacity planning documentation never could. In just two months, I learned that my “AI-heavy” platform rarely exceeds 4GB of RAM. An intricate Kubernetes setup I contemplated would have been a waste, managing empty containers instead of optimizing the real workload.
2. Hardcoded Configurations
Utilizing hardcoded constants for configuration like pricing and user limits may seem primitive, but it allows me to quickly access and modify parameters across my codebase. This method enables rapid redeployment—what would take a week to create in a formal configuration service gets done in just a few minutes of redeployment, drastically reducing engineering time.
3. SQLite as My Database of Choice
Running a multi-user web application on SQLite is unconventional, yet my database is a compact 47MB
