The Three-Month Rule: A Practical Approach to Non-Scalable Solutions in Tech Development

In the tech world, a commonly cited principle from entrepreneur Paul Graham emphasizes the importance of doing things that don’t scale. However, translating this concept into technical strategies, particularly in coding, is rarely addressed.

During my eight-month journey to develop an AI podcast platform, I devised a framework I call the “Three-Month Rule.” The essence of this approach is straightforward: any hack that isn’t designed for scalability is allowed to exist for a maximum of three months. After this trial period, it either proves its worth and is transformed into a more robust solution or is discarded entirely.

Typically, as engineers, we are conditioned to create scalable architectures from the outset. Our training often involves crafting beautiful systems that can support millions of users, utilizing design patterns and microservices. However, this mindset can lead to delays in startups, where focusing too heavily on scalability can become a costly form of procrastination.

Instead, my three-month framework compels me to prioritize simpler, more direct coding strategies that deliver results quickly. It allows me to glean meaningful insights about user needs without becoming mired in unnecessary complexities.

My Non-Scalable Solutions: Smart Choices That Yield Insight

1. Consolidated Infrastructure

Everything from the database to the web server operates on a single virtual machine (VM) with a modest $40 monthly cost. While it initially seems risky due to a lack of redundancy, this setup has provided me with invaluable data regarding my actual resource requirements. For instance, I discovered that my platform peaks at just 4GB of RAM. Building a complex Kubernetes setup would have been unwarranted, merely serving to manage unused containers.

When my system did experience crashes, which occurred a couple of times, I identified the real breakdowns, which were often surprising.

2. Simplified Configuration Management

Instead of using configuration files or environment variables, I opted for hardcoded constants throughout my codebase. By tracking changes in Git, I can swiftly locate any configuration value across the entire project. While it would typically require considerable engineering hours to build a dedicated configuration management system, I’ve only needed to make three adjustments in three months—resulting in a total redeployment time of about 15 minutes.

3. Using SQLite in a Production Environment

I made the unconventional choice to use SQLite for my web application, which has impressively handled 50 concurrent users with ease. This experience has taught me