Embracing the 3-Month Rule: A Pragmatic Approach to Non-Scalable Solutions

In the world of technology startups, the advice from Paul Graham to “Do things that don’t scale” is often cited but less frequently acted upon. Implementing this principle, particularly in the realm of coding, remains an under-discussed topic.

After dedicating eight months to developing my AI podcast platform, I’ve adopted what I call the “3-Month Rule” as a straightforward framework: every unscalable solution is granted a lifespan of three months. If it demonstrates its value within that time, it will be properly developed; if not, it will be discarded.

As engineers, we are conditioned to construct scalable solutions from the outset—utilizing sophisticated design patterns, microservices, and distributed systems that are engineered to accommodate vast numbers of users. However, this is often a mindset suited for big companies rather than startups. At early-stage ventures, focusing on scalable code can lead to costly procrastination, addressing user needs that might not even exist yet.

My 3-month rule encourages me to create simple, straightforward, and even “bad” code that allows me to launch quickly and gain invaluable insights into what users genuinely require.

Smart Infrastructure Hacks I’ve Implemented:

1. All-Encompassing VM Strategy

I’ve centralized my entire operation—a database, web server, background jobs, and Redis—on a single virtual machine costing $40 per month. While this eliminates redundancy and relies on manual backups, it has provided insights that would have been missed through traditional capacity planning. I’ve found that my platform’s peak usage demands only 4GB of RAM, revealing the impracticality of a complex Kubernetes setup that I initially considered.

2. Hardcoded Configuration

My configuration settings are intentionally hardcoded as constants throughout my codebase. As a result, any changes require a redeployment, but this approach lets me quickly find and track configuration values through version control history. Over three months, I’ve made only three configuration changes, translating to a mere 15 minutes of redeployment time—far superior to the 40 hours it would have taken to develop a dedicated configuration service.

3. Using SQLite for Production

Yes, I chose SQLite for a multi-user application. With a humble database size of 47MB, it’s capable of handling 50 concurrent users effortlessly. This experience taught me that my access patterns consist of 95% reads and only 5