Embracing the 3-Month Rule: A Practical Approach to Non-Scalable Solutions in Development

In the tech world, you’ve likely encountered the timeless advice from Paul Graham: “Do things that don’t scale.” However, the challenge lies in effectively implementing this advice, particularly within coding practices. After dedicating eight months to my AI podcast platform, I’ve established a straightforward framework: every unscalable method is allotted a mere three months. If it demonstrates value during that period, it is fully developed; if not, it is phased out.

As engineers, we’re often conditioned to prioritize scalability from the outset. We learn about sophisticated design patterns and complex architectures engineered to accommodate millions of users. Yet, this approach can often lead to unnecessary complications in a startup environment, where focusing on scalable solutions can feel like procrastination in disguise. Instead of catering to users that don’t yet exist, my three-month rule urges me to adopt simpler, straightforward coding practices that yield immediate results and reveal genuine user needs.

My Current Infrastructure Strategies and Their Surprising Benefits

1. Consolidated Operations on a Single Virtual Machine

Everything—from the database to the web server and background tasks—operates on a single $40/month virtual machine with no redundancy and manual backups.

This seemingly simplistic setup has been incredibly enlightening. I’ve gained valuable insights into my actual resource requirements far faster than through any capacity planning document. My platform, despite its heavily AI-focused nature, only peaks at 4GB of RAM. The cumbersome Kubernetes configuration I nearly built would have merely resulted in overseeing unutilized containers. Each time the server crashes, which has happened twice, I receive tangible data on actual failure points, often not aligning with my expectations.

2. Streamlined Hardcoded Configurations

PRICE_TIER_1 = 9.99
PRICE_TIER_2 = 19.99
MAX_USERS = 100
AI_MODEL = "gpt-4"

I operate without configuration files or environment variables, relying instead on constants scattered throughout my code. Adjusting any value requires redeploying the application.

This approach has a hidden strength: I can quickly search through my codebase for any configuration value and keep track of all changes through git history. In the past three months, I’ve only altered these settings three times, resulting in just 15 minutes of redeployment versus weeks of development time.

3. Utilizing SQLite in a Production Environment

Surprisingly, I