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

In the startup world, the phrase “Do things that don’t scale,” popularized by Paul Graham, is often repeated. Yet, when it comes to implementation, particularly in coding, this advice can feel ambiguous. After spending eight months developing my AI podcast platform, I’ve established the “3-Month Rule”—a practical framework that I adhere to when tackling unscalable solutions.

The Essence of the 3-Month Rule

As developers, we are conditioned to think about scalability from the outset. We envision performance-driven designs and robust architectures capable of accommodating vast user bases. However, in a startup environment, this forward-thinking approach can often devolve into unnecessary complexity, leading to a costly delay in product development.

My system mandates that any unscalable approach I adopt receives a trial period of just three months. During this time, the solution is allowed to prove its value. If it succeeds, it gets built out properly; if not, it is discarded. This disciplined focus enables me to create quick solutions that generate insights into what users genuinely need.

Infrastructure Hacks Worth Noting

Here’s a look at some of the unorthodox decisions I’ve made—decisions that may raise an eyebrow but have yielded valuable lessons.

1. Consolidated Resource Management

All my backend processes—including the database, web server, and caching—run on a single virtual machine (VM) that costs $40 a month. While it lacks redundancy and relies on manual backups, this setup has allowed me to fine-tune my resource requirements rapidly. Over two months, I discovered that my resource usage peaked at just 4GB of RAM. Instead of overengineering with complex solutions like Kubernetes, I gained real insights by allowing my system to fail, uncovering unexpected points of vulnerability.

2. Simplistic Configuration Management

In my codebase, configuration values are hardcoded directly into the source. Want to change a price or user limit? You’ll need to redeploy the entire application. While this approach lacks the sophistication of a dedicated configuration service, the immediate benefit has been clarity. I can swiftly locate any configuration parameter, and each change is documented explicitly in my version control history. In three months, I’ve only had to adjust these parameters three times, saving me countless hours of engineering work.

3. Utilizing SQLite for Production

I’ve chosen to run SQLite for a multi