Embracing the 3-Month Rule: A Tech Framework for Non-Scalable Solutions

In the world of startups, the conventional wisdom often echoes Paul Graham’s advice: “Do things that don’t scale.” Yet, the application of this principle in the realm of coding is seldom discussed. Over the past eight months, while developing my AI podcast platform, I’ve formulated a straightforward approach: each non-scalable solution is given a lifespan of three months. After this period, it either validates its worth and evolves into a robust implementation, or it gets discarded.

The startup Dilemma: When Scalability Becomes a Hindrance

As engineers, we’re trained to develop scalable systems from the outset. We often get lost in technical complexities like design patterns, microservices, and distributed architecture—concepts that cater to millions of users. However, within the startup ecosystem, pursuing these scalable frameworks can sometimes lead to costly procrastination. Frequently, we find ourselves optimizing for an audience that doesn’t yet exist, addressing challenges that may never arise. My 3-month rule compels me to produce simple, even “imperfect” code that can be deployed immediately, allowing me to gauge real user needs effectively.

Exploring My Current Non-Scalable Infrastructure Strategies

Here are some of the unconventional strategies I’ve adopted, emphasizing their practicality in a learning context.

1. Consolidated Resources on a Single VM

Currently, my entire stack operates on one $40/month virtual machine, consolidating the database, web server, background jobs, and caching mechanisms into a single unit. Although this setup lacks redundancy and relies on manual backups, it has provided invaluable insights into my resource requirements. Within just two months, I discovered that my “AI-heavy” platform peaks at 4GB of RAM. The intricate Kubernetes architecture I nearly implemented would have resulted in managing unnecessary resources.

2. Hardcoded Configuration Management

In my codebase, configuration values such as pricing tiers and user limits are hardcoded as constants rather than utilizing external config files or environment variables. This simplicity allows for rapid changes—redeployment takes only minutes compared to the extensive time required to build a configuration service. Despite the lack of bells and whistles, I can quickly search and track any configuration update through my version control system.

3. Using SQLite in a Multi-User Environment

My application relies on SQLite, managing a database size of merely 47MB, effortlessly supporting up to 50 concurrent users. This choice