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

In the world of startups and innovative projects, the phrase “do things that don’t scale” is frequently mentioned, particularly in the context of advice from the renowned Paul Graham. But how does one apply this principle in technical development, especially in coding? After dedicating eight months to building my AI podcast platform, I’ve established a practical framework that I’ve dubbed the “3-Month Rule.” Essentially, any unscalable workaround is allocated a three-month lifespan. At the end of this period, it either proves its worth to receive a proper implementation or it is abandoned.

The Reality of Startup Development

As engineers, we’re often conditioned to focus on scalability from the outset. We learn about diverse architecture types, from design patterns to distributed systems, all aimed at managing vast user bases efficiently. However, this forward-thinking perspective often leads to unnecessary complications in the startup environment, where anticipating future user demands can result in costly delays. My 3-Month Rule urges me to prioritize straightforward, albeit imperfect, coding solutions that provide immediate feedback and insight into user needs.

Current Infrastructure Hacks: Smart Simplifications

1. Unconventional Single-VM Setup

I have all critical operations—from my database to background tasks—running on a single $40/month virtual machine. Although this setup lacks redundancy and relies on manual backups, it has been revolutionary. In just two months, I gained invaluable insights into my actual resource consumption, revealing my platform’s peak needs with clarity. Rather than getting lost in the complexity of Kubernetes, I learned what truly impacts performance through direct experience.

2. Simplicity in Configuration Management

Gone are the days of sprawling configuration files. My constants, like pricing tiers and user limits, are directly coded into my application. This approach may seem archaic, but it provides unparalleled transparency and ease of auditing; tracking changes is as simple as inspecting git history. Over the past three months, I’ve only needed to update these values a handful of times, which highlights how much effort I would have unnecessarily invested in building a countdown service.

3. Embracing SQLite

In a notable departure from conventional wisdom, my multi-user web application runs on SQLite, and it performs admirably. With a database size of just 47MB, it effortlessly handles multiple concurrent users. This simple choice has taught me about my application’s actual access patterns, showing me that the majority of interactions are read operations