The 3-Month Rule: A Pragmatic Approach to Non-Scalable Solutions in Tech Development
In the world of startups, the age-old adage from Paul Graham, “Do things that don’t scale,” often resonates loudly. Yet, the challenge lies in translating this wisdom into actionable steps within the realm of coding. As a developer who has been refining an AI podcast platform for the past eight months, I’ve embraced a straightforward, yet effective framework: each unscalable solution has a lifespan of three months. After this period, the concepts are either validated and developed into robust features, or they are abandoned.
Rethinking Scalability
As engineers, we are generally conditioned to seek out solutions that are scalable from the outset. We get caught up in the allure of sophisticated systems involving design patterns, microservices, and distributed architectures that are meant to accommodate large user bases. However, in the context of a startup, this mindset can lead to a dauntingly premature pursuit of optimization. Such efforts often result in wasted resources and time spent addressing issues that may never arise.
My three-month rule compels me to create straightforward, sometimes “imperfect” code aimed at actual deployment. This approach has provided invaluable insights into user needs.
Current Infrastructure Strategies That Prove Effective
1. Consolidation into a Single Virtual Machine
Currently, my entire infrastructure, which includes the database, web server, background jobs, and Redis, operates on one $40-per-month VM. While this setup lacks redundancy, the knowledge I’ve gained in just two months has been enlightening. I’ve discerned that my AI-focused platform only requires around 4GB of RAM during peak usage. Had I proceeded with an intricate Kubernetes architecture, I would have been juggling empty containers instead of honing in on real challenges.
When the server fails (which has occurred twice), the immediate data reveals unexpected issues, providing rich learning moments.
2. Simple Hardcoded Configurations
My configuration is maintained through hardcoded constants like:
PRICE_TIER_1 = 9.99
MAX_USERS = 100
This approach eliminates the need for configuration files or environment variables, and any change requires a redeployment. The beauty of this simplicity? A quick search across my codebase allows for rapid adjustments, all traceable in version history. In the last three months, I’ve altered these values only three times, translating to a mere 15 minutes of downtime rather than potentially 40 hours of engineering
