Embracing the 3-Month Rule: A Practical Guide to Coding for Startups
In the world of startups, the advice from Paul Graham to “do things that don’t scale” often resonates deeply but can feel daunting. Specifically, how do we apply this mantra in the realm of coding? With eight months of experience building my AI podcast platform, I’ve crafted a straightforward approach that I call the “3-Month Rule.” This framework emphasizes that every temporary coding solution—regardless of its unscalable nature—gets a designated lifespan of three months. After this period, each solution must either demonstrate its value and transform into a more robust implementation or be phased out.
The Challenge of Scalable Solutions
As developers, we’re trained to prioritize scalable solutions from the get-go. The allure of intricate design patterns, microservices, and distributed systems is hard to resist, promising the ability to support millions of users. However, this is often a mindset suited to larger corporations. In the startup environment, focusing on scalability too early can lead to unnecessary complexity, forcing us to solve issues that haven’t yet arisen.
My 3-month timeframe encourages me to write straightforward, albeit imperfect, code that gets deployed quickly, allowing me to understand what my users truly need through firsthand experience.
Current Infrastructure Hacks: Smart Solutions in Disguise
1. Consolidation on a Single VM
Currently, everything from my database to the web server is operated on a singular $40/month virtual machine. While this setup lacks redundancy, it has offered invaluable insights into my real resource requirements. In just two months, I’ve discovered that my platform’s peak usage hovers around 4GB of RAM. Instead of wasting resources on an elaborate Kubernetes setup, I gather critical data when my system crashes, leading to revelations about vulnerabilities I wouldn’t have anticipated.
2. Simplistic Hardcoded Configurations
Instead of using configuration files and environment variables, I’ve opted for straightforward, hardcoded constants across my codebase. This may seem inefficient, but it allows me to quickly search for configurations and track changes conveniently through version control. The time saved by avoiding a dedicated configuration service far outweighs the rapid redeployment time—only minutes compared to the significant hours spent programming.
3. Using SQLite in Production
Surprisingly, my multi-user web application runs smoothly with SQLite, which is only 47MB in size. It effectively manages concurrent users with minimal complexity. Through this setup, I’ve learned
